## R Final ME InstControl Merged organized 1 Syllabus Mumbai University by munotes

## Page 2

Copy for information and necessary action : -

1. The Deputy Registrar, College Affiliations & Development Department

(CAD),

2. College Teachers Approval Unit (CTA),

3. The Deputy Registrar, (Admissions, Enrolment, Eligibility and

Migration Department (AEM),

4. The Deputy Registrar, Academic Appointments & Quality Assurance

(AAQA)

5. The Deputy Registrar, Research Administration & Promotion Cell

(RAPC),

6. The Deputy Registrar, Executive Authorities Section (EA)

He is requested to treat this as action taken report on the concerned

resolution adopted by the Academic Council referred to the above

circular.

7. The Deputy Registrar, PRO, Fort, (Publication Section),

8. The Deputy Registrar, Special Cell,

9. The Deputy Registrar, Fort Administration Department

(FAD) Record Section,

10. The Deputy Registrar, Vidyanagari Administration Department

(VAD),

Copy for information : -

1. The Director, Dept. of Information and Communication Technology

(DICT), Vidyanagari,

He is requested to upload the Circular University Website

2. The Director of Department of Student Development (DSD) ,

3. The Director, Institute of Distance and Open Learning (IDOL Admin),

Vidyanagari,

4. All Deputy Registrar, Examination House,

5. The Deputy Registrars, Finance & Accounts Section,

6. The Assistant Registrar, Administrative sub -Campus Thane,

7. The Assistant Registrar, School of Engg. & Applied Sciences, Kalyan,

8. The Assistant Registrar, Ratnagiri sub -centre, Ratnagiri,

9. P.A to Hon’ble Vice -Chancellor,

10. P.A to Pro -Vice-Chancellor,

11. P.A to Registrar,

12. P.A to All Deans of all Faculties,

13. P.A to Finance & Account Officers, (F & A.O),

14. P.A to Director, Board of Examinations and Evaluation,

15. P.A to Director, Innovation, Incubation and Linkages,

16. P.A to Director, Department of Li felong Learning and Extension (D LLE),

17. The Receptionist,

18. The Telephone Operator,

Copy with compliments for information to : -

19. The Secretary, MUASA

20. The Secretary, BUCTU.

## Page 3

AC – 11 July, 2022

Item No. – 6.36 (R)

Revised Syllabus for

M.E. ( Instrumentation and Control)

(Sem. - I to IV)

(Choice Based Credit System)

(With effect from the academic year 2022 -23)

## Page 4

## Page 5

Preamble

To meet the challenge of ensuring excellence in engineering education, the issue of quality needs to

be addressed, debated and taken forward in a systematic manner. Accreditation is the principal

means of quality assurance in higher education. The major emphasis of accreditation process is to

measure the outcomes of the program that is being accredited. In line with this Faculty of Science

and Technology (in particular Engineering) of University of Mumbai has taken a lead in

incorporating philosoph y of outcome -based education in the process of curriculum development.

Faculty resolved that course objectives and course outcomes are to be clearly defined for each

course, so that all faculty members in affiliated institutes understand the depth and appr oach of

course to be taught, which will enhance learner’s learning process. Choice based Credit and grading

system enables a much -required shift in focus from teacher -centric to learner -centric education since

the workload estimated is based on the investm ent of time in learning and not in teaching.

Italsofocusesoncontinuousevaluationwhichwillenhancethequalityofeducation. Credit assignment

for courses is based on 15 weeks teaching learning process, however content of courses is to be

taught in 12 -13 weeks a nd remaining 2 -3 weeks to be utilized for revision, guest lectures, coverage

of content beyond syllabus etc.

There was a concern that the earlier revised curriculum more focused on providing information and

knowledge across various domains of the said prog ram, which led to heavily loading of students in

terms of direct contact hours. In this regard, faculty of science and technology resolved that to minimize

the burden of contact hours, total credits of entire program will be of 170, wherein focus is not on ly on

providing knowledge but also on building skills, attitude and self -learning. Therefore, in the present

curriculum skill -based laboratories and mini projects are made mandatory across all disciplines of engineering

in second and third year of programs , which will definitely facilitate self -learning of students. The overall

credits and approach of curriculum proposed in the present revision is in line with AICTE model

curriculum.

The present curriculum will be implemented for M.E in Instrumentation and Control Engineering

from the academic year 202 2-2023.

## Page 6

Incorporation and implementation of Online Contents from NPTEL/ Swayam Platform

The curriculum revision is mainly focused on knowledge component, skill -based activities and project -

based activities. Self -learning opportunities are provided to learners. In the revision process this time in

particular Revised syllabus of ‘C’ scheme wher ever possible additional resource links of platforms such as

NPTEL, Swayam are appropriately provided. In an earlier revision of curriculum in the year 2012 and 2016

in Revised scheme ‘A' and ‘B' respectively, efforts were made to use online contents more appropriately as

additional learning materials to enhance learning of students.

In the current revision based on the recommendation of AICTE model curriculum overall credits are

reduced to 171, to provide opportunity of self -learning to learner. Learners are now getting sufficient time

for self -learning either through online courses or additional projects for enhancing their knowledge and

skill sets.

The Principals/ HoD’s/ Faculties of all the institute are required to motivate and encourage learners to us e

additional online resources available on platforms such as NPTEL/ Swayam. Learners can be advised to

take up online courses, on successful completion they are required to submit certification for the same. This

will definitely help learners to facilitate their enhanced learning based on their interest.

Dr. S. K. Ukarande

Associate Dean

Faculty of Science and Technology

Member, Academic Council, RRC in Engineering

University of Mumbai

## Page 7

From Chairman’s Desk

The overall technical education in our country is changing rapidly in manifolds. Now it is very much

challenging to maintain the quality of education with its rate of expansion. To meet present requirement a

systematic approach is necessary to build the strong technical base wi th the quality. Accreditation will

provide the quality assurance in higher education and to achieve recognition of the institution or program

meeting certain specified standards. The main -focus of an accreditation process is to measure the program

outcomes , essentially a range of skills and knowledge that a student will have at the time of graduation

from the program that is being accredited. Faculty of Science &Technology of University of Mumbai has

taken a lead in incorporating philosophy of outcome -based education in the process of curriculum

development.

I, as a Chairman, Board of Studies in Instrumentation Engineering of University of Mumbai, am happy to

state here that, Program Objectives (POs) were finalized for PG engineering program in Instrumentati on

Engineering, more than ten senior faculty members from the different institutes affiliated to University of

Mumbai were actively participated in this process. NBA has defined the following three POs for a graduate

of PG Engineering Program:

PO1: An ability to independently carry out research /investigation and development work to

solve practical problems.

PO2: An ability to write and present a substantial technical report/document.

PO3: Students should be able to demonstrate a degree of mastery over the area as per the

specialization of the program. The mastery should be at a level higher than the requirements

in the appropriate bachelor program

Dr. Alice N. Cheeran

Chairman,

Board of Studies in Instrumentation Engineering,

Member - Academic C ouncil, University of Mumbai

Dr. Mukesh D.Patil -Member BoS

Dr.Sharad P.Jadhav -Member BoS

Dr. Dipak D Gawali -Member BoS

Dr.M. J Lengare -Member BoS

Dr.Harish K. Pillai -Member BoS

## Page 8

Semester I

Course

Code Course Name Teaching Scheme (Contact Hours) Credits Assigned

Theory Pract. Tut. Theory Pract. Tut. Total

INC101 Advanced signal

processing for

Sensors 3 -- -- 3 -- -- 3

INC102 Higher

Mathematics for

Control

Engineering/Robu

st control 3 -- 3 -- 3

INPE101 Program Elective 1 3 -- -- 3 -- -- 3

INPE102 Program Elective 2 3 -- -- 3 -- -- 3

INIE101 Institute Elective 1 3 -- -- 3 -- -- 3

INL101 Program Lab -I -- 2 -- -- 1 -- 1

INSBL101 Skill Based Lab -I -- 4$ -- -- 2 -- 2

Total 15 06 -- 15 03 -- 18

Course

Code Course Name Examination Scheme

Theory Term

Work Pract

/

Oral Total

Internal Assessment End

Sem.

Exam Exam.

Durati

on (in

Hrs) Test-1 Test-2 Avg

INC101 Advanced signal

processing for

Sensors 20 20 20 80 3 -- -- 100

INC102 Higher

Mathematics for

Control

Engineering 20 20 20 80 3 -- -- 100

INPE101 Program Elective 1 20 20 20 80 3 -- -- 100

INPE102 Program Elective 2 20 20 20 80 3 -- -- 100

INIE101 Institute Elective 1 20 20 20 80 3 -- -- 100

INL101 Program Lab -I -- -- -- -- -- 25 25 50

INSBL101 Skill Based Lab -I

(MATLAB) -- -- -- -- -- 50 50 100

## Page 9

Total -- -- 100 400 -- 75 75 650

Semester II

Course

Code Course Name Teaching Scheme(Contact Hours) Credits Assigned

Theory Pract. Tut. Theory Pract. Tut. Total

INC201 State Estimation

and

Stochastic

Processes 3 -- -- 3 -- -- 3

INC202

Advanced Process

Control and

Automation 3 -- 3 -- 3

INPE201 Program Elective 3 3 -- -- 3 -- -- 3

INPE202 Program Elective 4 3 -- -- 3 -- -- 3

INIE201 Institute Elective 2 3 -- -- 3 -- -- 3

INL201 Program Lab -II -- 2 -- -- 1 -- 1

INSBL201 Skill Based Lab -II

(Python) -- 4$ -- -- 2 -- 2

Total 15 06 -- 15 03 -- 18

Course

Code Course Name Examination Scheme

Theory Term

Work Pract

/

Oral Total

Internal Assessment End

Sem.

Exam Exam.

Durati

on (in

Hrs) Test-1 Test-2 Avg

INC201 State Estimation

and

Stochastic

Processes 20 20 20 80 3 -- -- 100

INC202

Advanced Process

Control and

Automation 20 20 20 80 3 -- -- 100

INPE201 Program Elective 3 20 20 20 80 3 -- -- 100

INPE202 Program Elective 4 20 20 20 80 3 -- -- 100

INIE201 Institute Elective 2 20 20 20 80 3 -- -- 100

INL201 Program Lab -II -- -- -- -- -- 25 25 50

INSBL201 Skill Based Lab -II -- -- -- -- -- 50 50 100

Total -- -- 100 400 -- 75 75 650

Note 1: Skill Based Lab - I and II are focused on learning through experience. SBL shall facilitate the learner to

## Page 10

acquire the fundamentals of practical engineering in his or her specialization in a project -oriented

environment . The learning through skill-based labs can be useful in facilitating their research work and

hence useful in early completion of their dissertation work.

Semester III

Course

Code Course Name Teaching Scheme

(Contact Hours) Credits Assigned

Theory Pract. Tut. Theory Pract. Tut. Total

INMP301 Major Project:

Dissertation -I -- 20 -- -- 10 -- 10

Total 00 20 00 00 10 -- 10

Course

Code Course Name Examination Scheme

Theory Term

Work Pract/

Oral Total

Internal Assessment End

Sem

.

Exa

m Exam.

Durati

on (in

Hrs) Test-1 Test-2 Avg

INMP301 Major Project:

Dissertation -I -- -- -- -- -- 100 -- 100

Total -- -- -- -- -- 100 -- 100

Online Credit Courses

Course

Code Course Name Teaching Scheme

(Contact Hours) Credits Assigned

Theory Pract. Tut. Theory Pract. Tut. Total

XXOCC301 Online Credit Course - I -- -- -- -- -- -- 3

XXOCC301 Online Credit Course - II -- -- -- -- -- -- 3

Total -- -- -- 00 00 00 06

Note 2: It is mandatory to complete the Online Credit Courses (OCC) available on NPTEL / Swayam /MOOC or

similar platform approved by UoM . These two courses shall be completed in any semester I or II or III, but

not later end of the Semester III. University shall make a provision that credits earned with OCC - I and

OCC -II shall be accounted in the third semester grade -sheet with actual name s of courses. The learner shall

be allowed to take up these courses from his or her institute or organization / industry where his / her major

project is carried out. The students shall complete the courses and shall qualify the exam conducted by the

respec tive authorities/ instructor from the platform. The fees for any such courses and the corresponding

examination shall be borne by the learner.

Online Credit Course – I

The learner shall opt for the course in the domain of Research Methodology or Research & Publication

Ethics or IPR. The opted course shall be of 3 credits of equivalent number of weeks.

## Page 11

Online Credit Course –II

The learner shall opt for the course recommended by Faculty Advisor/ Project Supervisor from the

institute. The opted co urse shall be of 3 credits of equivalent number of weeks.

Semester IV

Course

Code Course Name Teaching Scheme

(Contact Hours) Credits Assigned

Theory Pract. Tut. Theory Pract. Tut. Total

INMP401 Major Project:

Dissertation -II -- 32 -- -- 16 -- 16

Total -- 32 -- -- 16 -- 16

Course

Code Course Name Examination Scheme

Theory Term

Work Pract/

Oral Total

Internal Assessment End

Sem

.

Exa

m Exam.

Durati

on (in

Hrs) Test-1 Test-2 Avg

INMP401 Major Project :

Dissertation -II -- -- -- -- -- 100 100 200

Total -- -- -- -- -- 100 100 200

Total Credits: 68

Note 3: The Dissertation -II submission shall not be permitted till the learner completes all the requirements

ME course.

Note 4: The contact hours for the calculation of load of the teacher for Major Project are as follows:

Major Project Dissertation I and II - 02 Hour / week / student

Guidelines for Dissertation -I

Students should do literature survey and identify the problem for Dissertation and finalize in consultation

with Guide/Supervisor. Students should use multiple literatures and understand the problem. Students should

attempt solution to the problem by analy tical/simulation/experimental methods. The solution to be validated

with proper justification and compile the report in standard format. Guidelines for Assessment of

Dissertation -I.

Dissertation -I should be assessed based on following points

∙ Quality of Literature survey and Novelty in the problem

∙ Clarity of Problem definition and Feasibility of problem solution

∙ Relevance to the specialization

∙ Clarity of objective and scope Dissertation -I should be assessed through a presentation by a panel of Internal

examiners and external examiner appointed by the Head of the Department/Institute of respective

Programme .

Guidelines for Assessment of Disserta tion II

Dissertation II should be assessed based on following points:

## Page 12

∙ Quality of Literature survey and Novelty in the problem

∙ Clarity of Problem definition and Feasibility of problem solution

∙ Relevance to the specialization or current Research / Industrial trends

∙ Clarity of objective and scope

∙ Quality of work attempted or learner contribution

∙ Validation of results

∙ Quality of Written and Oral Presentation

Students should publish at least one paper based on the work in the referred National/ International

conference /Journal of repute.

Dissertation II should be assessed by internal and External Examiners appointed by the University of

Mumbai .

Subject

Code Program Elective I Subject

Code Program Elective II

INPE1011 Advanced Biomedical Instrumentation INPE1021 Robust Control

INPE1012 Advanced Measurement Techniques

INPE1022 Expert System

INPE1013 Advanced analytical instrumentation INPE1023 Robotics and control

Subject

Code Program Elective III Subject

Code Program Elective IV

INPE2011 Electronics System Design INPE2021 Advanced Nuclear

Instrumentation

INPE2012 Advanced Fiber Optics and laser

Instrumentation INPE2022 Machine learning and Deep

learning

INPE201 3 Rehabilitation Engineering INPE202 3 MEMS and Nanotechnology

## Page 13

Subject Code Subject Name Credits

ISC101 Advanced Signal Processing for Sensors 03

Course Objectives:

· To give students knowledge in the field of advanced signal processing systems

required for processing the signals from various sensors.

· To give knowledge regarding applications of various types of sensors used for high

resolution measurement of various parameters.

Course Outcomes:

· The students will be able to understand the methodology and design of electronic

circuits utilized for processing the signals for various sensors.

Module Detailed content Hours

Prerequisite: Knowledge in the field of transducers and sensors, Basic

concepts in electronic signal processing

1 Classification of sensors and transducers: Input and output characteristics

of various transducers, variable resistance transducer and its equivalent

circuit, potentiometers, their construction and performance, variable

inductance and variable capacitance transducers, their construction and

performance, Piezoelectric transducer. 06

2 Design techniques for sensor signal conditioning: Sensor and signal

conditioning for strain, force, pressure, flow and temperature measurement,

Bridge configurations, Amplifying and linearizing bridge outputs, Driving

bridge circuits. Ratio metric techniques.

08

3 High impedance sensors: Photodiodes and high impedance charge output

sensors, Signal conditioning of high impedance sensors, Chemical and

Biosensors.

06

4 Positioning, motion and temperature sensors: LVDT, Hall effect magnetic

sensors, optical encoder Accelerometer, RTDs, thermistors, thermocouples,

semiconductors temperature sensors and their signal conditioning.

08

5 Micro -sensors and smart sensors: Construction, characteristics, and

applications. 04

## Page 14

6 Radioactivity detectors and Counting systems:

Gas filled, Scintillation and Semiconductor detectors, preamplifiers,

Shaping amplifiers, Single Channel analyzer, Multi -channel analyzer.

07

Assessment:

Internal: Assessment consists of two tests out of which; one should be compulsory class test (on

minimum 02 Modules) and the other is either a class test or assignment on live problems or course

project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions to be

set each of 20 marks, out of these any four questions to be attempted by students. Minimum 80% syllabus

should be covered in question papers of end semester examination.

References:

1. H.K.P Neubert ―Instrument Transducers Oxford Herman University Press Eighth Impression 2008.

2. Ramon Pallas -Arenyand Johan G. Webster ―Sensor and Signal Conditioning‖ John Wiley,

New York 1991.

3. Dan Sheingold -Editior ―Transducer Interfacing Handbook‖, Analog Devices Inc 1980

4. ―High Speed Design Technique‖ Analog Device Inc 1996

5. Jacoba Fraden ―Handbook of Modern Sensors ―2nd Edition, Springer -Verlag.New York 1996

6. Jerald G.Graeme ―Photodiode Amp lifiers And Op -Amp Solution‖, Mc Graw Hill 1995

7. Harry L. Trietly, ―Transducers in Mechanical and Electronic Design‖, Marcel Dekker Inc 1986

8. Dan Shiengold, ―Non Linear Circuits Handbook‖, Analog Device Inc

9. Walt Kester -Editior, ―System Application G uide‖, Analog Devices Inc 1993

10. IMEGA, ―Temperature Measurement Handbook‖, Omega Instruments Inc

11. Henry Ott, ―Noise Reduction Technique In Electronic Systems‖, N.Y.John Wiley And Sons 1988

12. Ralph Morrison,‖Grounding And Shielding Technique‖, Fourt h Edition,John Wiley,1998

13. G.F.Knoll ,―Radiation detection and measurement‖, John Wiely and Sons, 2nd edition, 1998.

## Page 15

Subject Code Subject Name Credits

ISC102 Higher Mathematics for Control Engineering 3

Course Objectives:

· To introduce different methods of solving systems of linear equations

· Introduce concept of Linear Vector Spaces

· To present the concept of Orthogonality and Quadratics Forms

Course Outcomes:

· Demonstrate ability to solve systems of linear equations

· Demonstrate ability to work with Vector Spaces

· Demonstrate ability to get least square solutions to systems

· Demonstrate ability to effect linear transformation

Module Detailed content Hours

Prerequisite: Knowledge about Matrices, Matrix,

ElementaryOperations, Determinants and Matrix Inverse

1 Linear Equations in Linear Algebra: Systems of Linear

Equations,Gaussian Elimination, Row Reduction , Echelon Forms , LU

Factorization.

06

2 Euclidean Vector Spaces: Euclidean n -Space, Linear transformation

from Rn to Rm, Properties of Linear Transformations from Rn to

Rm,Linear Transformation.

06

3 General Vector Spaces: Real Vector Spaces, Subspaces,

LinearIndependence, Basis and Dimension, Row Space, Column Space

and Nullspace, Rank, Nullity and Change of basis.

07

4 Eigenvalues and Eigenvectors: Eigenvectors and Eigenvalues, The

Characteristic Equation, Diagonalization, Eigenvectors and

LinearTransformations, Complex Eigenvalues, Discrete Dynamical

Systems.

07

5 Orthogonality and Least Squares: Inner Product, length and

Orthogonality, Orthogonal Sets, Orthogonal Projections, The Gram -

Schmidt Process, Least –Square Problems, Applications to Linear

Models, Inner Product Spaces, Applications of Inner Product Spaces.

07

## Page 16

6 Symmetric Matrices and Quadratic Forms: Diagonalization of

Symmetric Matrices, Quadratic Forms, Constrained Optimization, The

Singular Value Decomposition, Application to Image Processing and

Statistics.

06

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class

test (on minimum 02 Modules) and the other is either a class test or assignment on live problems

or course project.

End Semester Examination: Some guidelines for setting the q uestion papers are as, six questions

to be set each of 20 marks, out of these any four questions to be attempted by students.

Minimum 80% syllabus should be covered in question papers of end semester examination.

References:

1. Anthanasios Papoulis, ―Probability, random Variable & Stochastic Processes‖ 3rd Edn,

McGraw Hill, Inc 1995

2. Gantmacher, Feliks R.‖the theory of Matrices Vol.I and II‖ Chelsia Publishing Co.1959

3. Gantmacher F.R. ―Application of Theory of Matrices‖

4. Hoffman K. & R. Kunez, ―Linear Algebra‖ 2nd Edn, Printice Hall 1971

5. Howard Anton, ―Elementary Linear Algebra‖ - Wiley Student End, 2011

## Page 17

Program Elective -I

Subject Code Subject Name Credits

INPE1011 Advanced Biomedical Instrumentation 03

Course Objectives:

· To introduce concepts of advanced biomedical instruments used in hospitals.

· To study the design considerations of various signal conditioning systems for

measurement of Bio -signals like ECG, EEG and EMG.

· To study the concept behind various Advanced Medical imaging techniques. Course Outcomes:

· The students should be able to understand the principle and working of various

advanced biomedical instruments.

· The students should be able to design signal conditioning systems for bio -signal

measurements.

· The students should be able to apply concepts of biomedical techniques for various

applications.

· The students should be able to understand the concept and working of various

advanced medical image acquisition and reconstruction techniques.

Module Detailed content Hours

Prerequisite: Knowledge of Anatomy and Physiology of Human Systems,

Knowledge of various Bio -signals and their basic Measurement techniques,

Knowledge of basic principle of Medical Imaging Techniques

1 Instrumentation for Bio -Potential Recording: Sensors, Biopotential

Amplifiers like Chopper Amplifiers, Isolation Amplifiers and Advanced

Instrumentation Amplifiers, Signal Conditioning Circuit designing for ECG,

EEG and EMG, Multi -Channel Data Acquisition System .

10

2 Diathermy in Medicine: Electro Surgical Diathermy, Short Wave

Diathermy, Microwave Diathermy and Ultrasound

Diathermy, Lithotripsy.

05

3 Cardiac and Neuro -Assist Devices: Cardiac Pace

Makers -constructional details and design, Internal and External

Defibrillators with Design, Stimulation Electronics – Nerve and Muscle

Stimulators .

06

4 Telemetry and Telemedicine: Introduction to Telemetry System, Types of

Wireless, Power and Data Transmission System, Receiver and Transmitter

specifications, Telemedicine.

06

## Page 18

5 Advanced Medical Imaging Systems: CT Scanning Systems – tube design,

types of Gantries, Image Reconstruction Techniques in Tomography.

MRI – Image Acquisition and Reconstruction Techniques.

Nuclear Imaging – Scanners, Gamma Camera, Positron Emission

Tomography (PET), Single Photon Emission Computed Tomography

(SPECT).

08

6 Laser Application in Medicine: Types of Lasers, Properties of Lasers and

Interaction of Lasers with tissues, Basic Endoscope System and its

characteristics.

04

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class test (on

minimum 02 Modules) and the other is either a class test or assignment on live problems or course

project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions

to be set each of 20 marks, out of these any four questions to be attempted by students.

Minimu m 80% syllabus should be covered in question papers of end semester

examination.

References:

1. Jacobsons and Webster, ―Medicine and Clinical Engineering‖, PHI, 1981.

2. Carr and Brown, ―Introduction of Biomedical Equipment Technology‖, PHI, 1981.

3. Jacob Kline, ―Handbook of BioMedical Engineering‖, Academic Press, 1988.

4. J B Gupta, ―A course in Electronic and Electrical Measurement and

Instrumentation‖, S K Kataria and Sons, 1999.

5. Steve Webb, ―The Physics of Medical Imaging‖, Taylor & Francis , New York, 1988.

6. Norris, A.C., ―Essential of Telemedicine and Telecare‖, Wiley, 2002.

## Page 19

Subject Code Subject Name Credits

INPE1012 Advanced Measurement Techniques 03

Course Objectives:

To provide knowledge to the students regarding various methods used for high resolution

measurement of various parameters like voltage, current, resistance, inductance, capacitance,

time, frequency and phase difference.

Course Outcomes:

· Understand principles and methods used for measurement of various parameters.

· Make use of proper methods of measurement depending upon requirement of resolution,

accuracy and speed of measurement.

Module Detailed content Hours

Prerequisite: Basic knowledge of electronic measurements,

analog and digital circuits.

1 High resolution measurement for electrical components:

Analog and digital techniques for high resolution measurement

of Resistance, Inductance, Capacitance. Various bridge circuits

and auto balancing methods. Polar and Cartesian type

impedance meters. Tan delta measurement.

10

2 High resolution time measurement: Philosophy of digital and

microprocessor/ microcontroller -based instruments.; Time

measurement techniques: Time standards; Measurement of time

interval between events, order of events, Vernier technique,

very low time, period, phase, time constant measurements

06

3 Frequency measurement techniques: Frequency, ratio and

product, high and low frequency measurements; Deviation

meter and tachometer, Peak/valley recorder.; 06

4 Programmable circuits: Programmable resistors, amplifiers,

filters; Programmable amplifiers as DACs

04

5 Applications of ADCs and DACs: Application of various

types of ADCs and DACs in measurement techniques; DVM

and its design; Voltage and current ratio measurements.

08

6 Sampling theory and applications: Modulation

index meter, Sampling theory and its application in

05

## Page 20

current, voltage, power and energy measurements.

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class test (on

minimum 02 Modules) and the other is either a class test or assignment on live problems or course

project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions

to be set each of 20 marks, out of these any four questions to be attempted by students.

Minimum 80% syllabus should be cover ed in question papers of end semester examination.

References:

1. T. S. Rathore, ―Digital Measurement Techniques‖, Narosa Publishing House, 1996.

2. B. S. Sonde, ―Monographs on System Design using Integrated Circuits‖, Tata Mc -Graw

Hill, 1974.

3. D. J. DeFatta, J. G. Lucas, ―Digital Signal Processing‖, J Wiley and Sons, 1988.

## Page 21

Subject Code Subject Name Credits

INPE1013 Advanced Analytical Instrumentation 03

Module Detailed content Hours

1 Spectrophotometric /Gas analyzers

IR/NIR/UV/VIS analyzers – Cells, Detectors, Signal Processing, Calibration,

Minimization of Interference and Comparative Analysis of Analyzers &

Gaseous Components Detected

Hydrocarbon analyzers - Flame Ionization Detectors, Principle of Operation

Oxygen and NO/NO2 analyzers - Signal Processing, Calibration, Minimization

of Interference, Applications

Sampling Systems – Desirable Features, Filters, Flow and Pressure regulators,

Coolers, Condensers, Vacuum Pumps, Blowback Cleaning System, Exhaust

Practices. 07

2 Electrochemical/Liquid Analyzers pH Analyzers – Measurement and

Compensation, Pre-amplifiers, Transmitters, Measurement cells.

Conductivity Analyzer – Cells and Cell Constant, Effect of temperature on

measurement calibration, acid and alkali titration meas urement. Redox

Analyzer - Principle of operation, components of analyzers and applications.

Trace Oxygen and Residual Chlorine Analyzer - Principle of operation,

components of analyzers and applications. 08

3 Compositional Process Analyzer Gas and Liquid Chromatography –

columns, gas and liquid detectors, data processing, process chromatography,

calibration and application.

Mass Spectrometry – Components, different types, sampling systems,

calibration and applications. 07

4 Biomedical Spectroscopy -Types of Biomolecules, different spectroscopic

analysis techniques, principle of operation, components, data processing and

applications, Blood gas analyzers 06

## Page 22

5 Environmental Analy zers: Waste Water Environmental Analysis, analy zer’s

principle of operations & components, calibration and applications. 04

6 Nuclear Magnetic Resonance Spectroscopy - Principle of operation,

components, sensitivity enhancement techniques and different types of NMR

Spectrometers with applications. 06

REFERENCES

1. B. G. Liptak, “Instrument Engineers’ Handbook: Process Measurement and Analysis”,

Butterworth Hieneman, Boston, 1995.

2. D.M. Considine, “Process Instruments and Control Handbook”, 4th edition, McGraw Hill

New York, 1993.

3. K. J. Clevett, “Process Analyzer Technology”, John Wiley & Sons, 1986, New York.

4. Gas Analysis – Book 14 Fisher Rosemount Educational Services.

5. G. K. Macmillan, “pH Measurement and Control”, ISA 1994.

6. pH and Conductivity – Book 13 Fisher Rosemount Educational Services.

7. R.E. Sherman, “Analytical Instrumentation”, TWI Press, Indiana, 1996.

8. Meyers, “Encyclopedia of Analytical Chemistry”.

9. Instruction Manuals at http:// www.frco.com/proanalytic/library/publicmanuals.html.

## Page 23

Program Elective II

Subject Code Subject Name Credits

ISE1021 Robus t Control 03

Course Objectives:

● To study the effect of disturbance, parametric uncertainties and model errors on the

● stability of the system.

● To study the robust control techniques such as a control based on Kharitonov theorem,

● internal model control and introduction to Quantitative feedback technique for t he system

● with parametric uncertainties and external disturbances.

● To study the sliding mode control for asymptotic stability in presence of disturbances.

Course Outcomes:

● The students should be able to understand the robustness properties of the system ag ainst

uncertainties.

● Students should be able to design robust control that overcomes parametric uncertainties.

● Students should be able to design the internal model control for uncertain systems.

● Students should be able to understand the concept of Quantitative feedback techniques.

● Students should be able to design the sliding mode control for uncertain systems.

Module Detailed content Hours

Prerequisite: Regulators and Servo Mechanism, Concepts in State -

space analysis, Controllability and Observability.

1 Introduction to Sliding Mode Control : Main Concepts of Sliding

Mode Control, Chattering Avoidance: Attenuation and Elimination,

Concept of Equivalent Control, Sliding Mode Equations, The Matching

Condition and Insensitivity Properties, Conventional Sliding Mode

Controller Design 06

2 Conventional Sliding Modes: Introduction, Filippov Solution, Concept

of Equivalent Control, State -Feedback Sliding Surface Design, Regular

Form, Eigenvalue Placement, Quadratic Minimization, State -Feedback

Relay, Control Law Design, Single -Input Nominal Systems, Single -

Input Perturbed Systems, Relay Contr ol for Multi -Input Systems. 08

3 Interval Polynomials: Kharitonov's Theorem: Kharitonov's Theorem

for Real Polynomials, Kharitonov's Theorem for Complex

Polynomials, Robust State Feedback Stabilization 06

## Page 24

4 Internal Model Control (IMC): Introduction to Model -Based Control,

Practical Open -Loop Controller Design, Generalization of the Open -

Loop Control Design Procedure, Model Uncertainty and Disturbances,

Development of the IMC Structure, IMC Background, The IMC

Structure, The IMC Design Procedure, Effect of Model Uncertainty and

Disturbances, Improving Disturbance Rejection Design 07

5 The IMC -Based PID Control : Background, The Equivalent Feedback

Form to IMC, IMC -Based Feedback Design for Delay -Free Processes,

IMC -Based Feedback Design for Processes with a Time Delay,

Summary of IMC -Based PID Controller Design for Stable Processes,

IMC -Based PID Controller Design for Unstable Processes 08

6 Introduction to Quantitative Feedback Theory: Quantitative

Feedback Theory (QFT), Why Feedback, QFT Overview, QFT Design

Objective, Structured Parametric Uncertainty, Control System

Performance Specifications, QFT Design Overview, QFT Basics, QFT

Design, Insight to the QFT Technique, Open -Loop Plant, Closed -Loop

Formulation, Benefits of QFT. 04

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class test (on

minimum 02 Modules) and the other is either a class test or assignment on live problems or course

project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions

to be set each of 20 marks, out of these any four questions to be attempted by students. Minimum 80%

syllabus should be covered in question papers of end semester examination.

Referenc es:

1. S. P. Bhattacharyya, H. Chapellat, and L. H. Keel. ―Robust control: the parametric approach," Upper

Saddle River (1995).

2. Manfred Morari and Evanghelos Za_riou, ―Robust process control," Vol. 488. Englewood Cliffs, NJ,

Prentice hall, 1989.

3. B. W ayne Bequette, ―Process Control: Modeling, Design and Simulation," Prentice Hall Professional,

2003.

4. Constantine H. Houpis, Steven J. Rasmussen and Mario Garcia -Sanz, ―Quantitative feedback theory:

fundamentals and applications," CRC Press, 2005.

5. Ode d Yaniv, ―Quantitative feedback design of linear and nonlinear control systems”, Vol.509.

Springer Science & Business Media, 2013.

6. Yuri Shtessel, Christopher Edwards, Leonid Fridman and Arie Levant, ―Sliding mode control

and observation," New York, USA: Birkhuser, 2014.

7. Christopher Edwards and Sarah Spurgeon, ―Sliding mode control: theory and applications, CRC

Press, 1998.

8. Dorf, Richard C., and Robert H. Bishop, ―Modern control systems," Prentice Hall, 2011

## Page 25

Subject Code Subject Name Credits

INEP1022 Expert Systems 03

Course Objectives:

● To give knowledge to the students regarding Neural Networks and their applications in

control engineering.

● To familiarize the students with concepts in Fuzzy Logic and their applications in

control engineering .

Course Outcomes:

● Students will be able to understand concepts in Neural Networks and their applications

in control engineering.

● Students will be able to understand concepts in Fuzzy logic and their applications in

control engineering.

● Students will be able to understand concepts in Artificial intelligent systems such as

perceptrons.

Module Detailed content Hours

Prerequisite: Basic knowledge in computer scienc e and Control

Engineering

1 Introduction to Neural Networks: Artificial Neural Networks: Basic

properties of Neurons; Neuron Models; Feedforward networks -

Perceptrons; Widrow -Hoff LMS algorithm; Multiplayer networks - Exact

and approximate representation; Back propagation algorithm; variants of

Back propagation; Un supervised and Reinforcement learning; Symmetric

Hopfield networks and Associative memory; Competitive learning and

self-organizing networks, Hybrid Learning; Computational complexity of

ANNs.

08

2 Neural Networks Based Control: ANN based control: Introduction:

Representation and identification; modeling the plant, control structures -

supervised control, Model reference control, Internal model control,

Predictive control: Examples - Inferential estimation of viscosity a

chemical process; Auto - tuning feedback control; industrial distillation

tower.

06

3 Introduction to Fuzzy Logic: Fuzzy Controllers: Preliminaries -Fuzzy

sets and Basic notions - Fuzzy relation calculations - Fuzzy members -

Indices of Fuzziness - comparison of Fuzzy quantities -Methods of

determination of membership functions.

06

4 Fuzzy Logic Based Control: Fuzzy Controllers: Basic construction of

fuzzy controller - Analysis of static properties of fuzzy controller - Analysis

of dynamic properties of fuzzy controller - simulation studies - case studies

- fuzzy control for smart cars.

08

## Page 26

5 Neuro - Fuzzy and Fuzzy: Neural Controllers: Neuro - fuzzy systems; A

unified approximate reasonin g approach - Construction of role bases by

self-learning : System structure and learning algorithm - A hybrid neural

network based Fuzzy controller wit h self-learning teacher. Fuzzified

CMAC and RBF network based self -learning controll ers.

06

6 Artificial Neural Networks: Supervised Learning: Introduction and how

brain works, Neuron as a simple computing element, The perceptron,

Backpropagation networks - architecture, multilayer perceptron 05

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class test (on

minimum 02 Modules) and the other is either a class test or assignment on live problems or course

project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions

to be set each of 20 marks, out of these any four questions to be attempted by students.

Minimum 80% syllabus should be covered in question papers of end semester

examination.

References:

1. Bose & Liang, ― Artificial Neural Networks ―, Tata Mcgraw Hill, 1996

2. Kosco B, ― Neural Networks and Fuzzy Systems : A Dynamic Approach to Machine

Intelligence, Prentice Hall of India, New Delhi, 1992.

3. Klir G.J. and Folger T.A., Fuzzy sets, ― Uncertainty and Information ― , Prentice

Hall of India, New Delhi, 1994.

4. Simon Haykin - ― Neural Networks ―, ISA, Research Triangle Park, 1995

## Page 27

Subject Code Subject Name Credits

INPE1023 Robotics and Control 03

Course Objectives:

· To introduce robot terminologies and robotic sensors

· To educate on direct and inverse kinematics

· To introduce robot control techniques

Course Outcomes:

● Students would be able to understand the concepts behind various robotic sensors and

manipulators.

● Students would be able to understand the kinematics and control strategies behind robot

movement.

● Students would be able to apply robots for various applications.

Module Detailed content Hours

Prerequisite: Knowledge of basic control strategies, Knowledge of working of

basic controllers, Knowledge of basic programming languages like C, C++

1 Robot Organization: Coordinate transformation, kinematics and inverse

kinematics, Trajectory planning and remote manipulation. 06

2 Robot Hardware: Robot sensors, Proximity sensors, Range sensors, Visual

sensors, Auditory sensors, Robot manipulators, Manipulator dynamics,

Manipulator control, Wrists, End efforts, Robot grippers.

09

3 Robot and Artificial Intelligence: Principles of AI, Basics of learning, Planning

movement, Basics of knowledge representations, Robot programming languages.

08

4 Robot Vision System: Principles of edge detection, determining optical flow

and shape, Image segmentation, Pattern recognition, Model directed scene

analysis.

06

5 Robot Control System: Linear control schemes, joint actuators, decentralized

PID control, Computed torque control, force control, hybrid position force

control, Robot control using voice and infrared.

06

6 Robot Application: Overview of robot applications. Prosthetic devices. Robots

in material handling, processing assembly and storage.

04

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class

test (on minimum 02 Modules) and the other is either a class test or assignment on live problems

or course project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions

to be set each of 20 marks, out of these any four questions to be attempted by students.

## Page 28

Minimum 80% syllabus should be covered in question papers of end semester

examination.

References:

1. Koren, ―Robotics for Engineers‖, McGraw Hill International Company, Tokyo, 1995.

2. Vokopravotic, ―Introduction to Robotics‖, Springer, 1988.

3. Rathmill. K., ―Robot Technology and Application‖, Springer, 1985.

4. Charniak and McDarmott, ―Introducation to Artificial Intelligence‖, McGraw Hill, 1986.

5. K. S. Fu, R. C. Gonzally, C.S. G. Lee, ―Robotics Control, Sensing, Vision and

Intelligence‖, McGraw Hill Book Company, 1997.

6. Barru Leatham, Jones, ―Elements of Industrial Robotics‖, Pittmann Publishing, 1987.

7. Mikell P. Groover, Mitchell Weiss, Roger. N. Nagel, Nicholas G. Odrey, ―Industrial

Robotic Technology Programming and Applications‖, McGraw Hill B ook Company,

1986.

## Page 29

Subject Code Subject Name Credits

INL101 Program Lab -I 01

E Title

1 Linearizing circuit for ―single element‖ varying bridge.

2 Kelvin sensing system to drive remote bridges.

3 Active low pass, band pass and high pass filters for transducer signal processing.

4 Use of high-resolution ADC for transducer signal processing.

5 Simulation of boiler start -up process control using PLC

6 Simulation of paint manufacturing process using PLC

7 Study of SCADA (HMI) software

NOTE: Perform any six experiments from above list and two experiments from Department

Elective Course.

Term work: Term work consists of performing 08 practicals mentioned as above. Final

certification and acceptance of the term work ensures satisfactory performa nce of laboratory

work

Assessment:

End Semester Examination: Practical/Oral examination is to be conducted by pair of

internal and external examiners.

## Page 30

Subject Code Subject Name Credits

INSBL101 Skill Based Lab -I 01

Expt no. Title

1 Experiments in MATLAB/Scilab for Computation of Eigenvalues, Eigen vectors,

different types of norms etc.

2 QR Decomposition

3 LQ Decomposition

4 Gram Schmidt Orthogonalization

5 Design the sliding mode control for SISO systems

6 Design the IMC controller for the —

a) First order delay system

b) First order NMP system

7 Design PID controller based on IMC controller

8 Design state feedback control for interval systems.

NOTE: Perform any six experiments from above list and two experiments from Department

Elective Course.

Term work: Term work consists of performing 08 practical mentioned as above. Final

certification and acceptance of the term work ensures satisfactory performa nce of laboratory

work

Assessment:

End Semester Examination: Practical/Oral examination is to be conducted by pair of

internal and external examiners.

## Page 31

Sem-II

Subject Code Subject Name Credits

INC201 State Estimation and Stochastic Processes 03

Course Objectives:

· To study the concept of Stochastic Processes, Monte Carlo Simulation and fractional calculus

· To study the concept of Kalman filtering

Course Outcomes:

· The students should be able to understand the Stochastic Properties of random variables in

terms of pdf.

· Students should be able to understand the concept of stochastic processes

· Students should be able to understand concept of least square estimation

· Students should be able to realize the significance of Kalman filter and its applications

to linear and nonlinear systems.

Module Detailed content Hours

Prerequisite: Knowledge about concept of probability and Random Variable,

Knowledge about concept of state and state space models of systems

1 Random Variables: Introduction to Random Variables, Probability

Distribution Function, Probability Density Function, Exponential Distribution,

Gaussian Distribution, Binomial Distribution, Poisson Distribution, Two

Dimensional Random Variables, Joint Probability, Marginal Density Function,

Conditional Probability and Independence,

Correlation, Covariance, Introduction to n -dimensional Random Variables.

10

2 Stochastic Processes: Definition, Statistics of Stochastic Processes, Types of

Stochastic Processes, Random Walk, Markov Process, Brownian Motion,

Poisson Process, Concept of Monte Carlo Simulation, Monte Carlo Simulation

of Stochastic Processes such as Random Walk. Correlatio n functions, Power

Spectrum, White Noise,

Linear Systems with Stochastic input.

08

Parameter Estimation: Point Estimation, Optimal Estimates, Acceptable

Estimates, Least Squares Estimation: The deterministic point of view (Gauss),

Sequential Bayes Theorem, Linear Minimum

## Page 32

3 Mean -square -error Estimation: Vector case sequential MMSE Estimation. 08

4 The Discrete -time Kalman Filter: Propagation of states

and covariances, Derivation of the discrete -time Kalman filter,

Kalman filter properties, Divergence issues

05

5 Nonlinear Kalman Filtering: The extended Kalman Filter, The Unscented

Kalman Filter, General Unscented transformations, The Simplex unscented

transformation, The spherical unscented transformation, Introduction to

Particle filtering

05

6 Fractional Calculus: Introduction to Fractional Calculus, Functions for the

Fractional Calculus, Riemann -Liouvelli fractional derivative(Left Hand

Definition), Caputo definition of fractional derivative (Right Hand Definition),

Fractional random walk, Application of fractional calculus to engineering

systems 03

Assessment:

Internal: Asse ssment consists of two tests out of which; one should be a compulsory class

test (on minimum 02 Modules) and the other is either a class test or assignment on live problems

or course project .

End Semester Examination: Some guidelines for setting the ques tion papers are as, six questions

to be set each of 20 marks, out of these any four questions to be attempted by students.

Minimum 80% syllabus should be covered in question papers of end semester examination.

References:

1. Starks and Woods, ―Probability and Random Processes with applications to Signal

Processing, Phi, 2002.

2. Simon Haykins, ―Adaptive filter theory‖, Pearson 2012

3. W.C.Van Etten, ― Introduction to Random signals and noise‖, Wiley 2009

4. G.N. Saridis, ― Stochastic Processes, Estimation a nd Control‖, Wiley 1995

5. Meditch. J., ― Stochastic Linear Estimation and Control‖, Tata Mcgraw Hills, 1969

6. Paupolis, ―Probability , Random Variables and Stochastic Processes, Mc -Grawhill, 1995

7. Shantanu Das, ―Functional Fractional Calculus‖ 2nd Edn, Springer Verlag, Germany, 2012

8. Dan Simon, ―Optimal State Estimation‖ – Wiery 200 6

## Page 33

Subject Code Subject Name Credits

INC202 Advanced Process Control and Automation 03

Course Objectives:

· To study the concepts of process modeling

· To study the effect of constraints and interaction between different loops

· To study the sizing of PLC and DCS.

· To study the knowledge about safety Instrumented Systems and advances in intrinsic safety.

Course Outcomes:

· The students should be able to design the pr ocess and behavioral model of the process.

· The students should be able to select appropriate control configuration to minimize

interaction between different loops

· The students should be able to design PLC and DCS based systems.

· The students should be able to calculate Safety Integrity Level for a given process.

Module Detailed content Hours

Prerequisite: Basic knowledge of Process control and automation tools

such as PLC, DCS and SCADA

1 Process Dynamics and Control: Fundamentals of process modeling,

Design for process modeling and behavioral model, Linearisation of

model equations - Level process, evaporation and chemical reactor

model. Dynamics of CSTR, Heat exchanger and evaporator.

06

2 Multivariable control: Constraint Control, SISO constraint control,Signal

selectors, Relative gain analysis, steady state decoupling, dynamic

decoupling.

05

3 Integrated Automation: Process and factory automation, PLC, DCS and

SCADA - programming, selection and sizing, PLC networking, PLC -

HMI interfacing, Installation and troubleshooting.

10

4 Buses and Networks: Introduction to networks in Industrial Automation,

PLC Proprietary and open networks, hardware selection for Fieldbus

systems, Fieldbus advantages and disadvantages, Limitations of open

networks. Design and installation of Field Bus ori ented Industrial

Communication Networks - Foundation Fieldbus, Profibus PA,

Devicenet, As -i segments in Hazardous and Non -Hazardous area.

08

## Page 34

5 Safety Instrumented System: Life cycle model of Safety Instrumented

System, technologies, SIL calculation methods, SIL -calculation of PFD,

RRF etc., Phases of SIS overall implementation and reliability.

06

6 Advanced intrinsic safety: Entity concept, FISCO, High power trunk,

Dynamic arc recognition and termination technology with advantages

and disadvantages.

04

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class

test (on minimum 02 Modules) and the other is either a class test or assignment on live problems

or course project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions to be

set each of 20 marks, out of these any four questions to be attempted by students. Minimum 80% syllabus

should be covered in question papers of end semest er examination.

References:

1. Myke King, ―Process control -A practical approach‖, John Wiley, !st edition,2011.

2. Bela G Liptak, ― Instrument Enginner‘s Handbook -Process software and digital networks‖,

CRC press, ISA,3rd edition,2002.

3. Bela G Liptak, ―Optimisation of Unit operaion‖, ISA.

4. Bela G Liptak, ― Instrument Enginner‘s Handbook -Process Control‖, Chilton Book

Company, 3rd edition.

5. Gary Dunning, ―Introduction to Programmable Logic controller‖, Thomas Learning,

edition, 2001.

6. Thomas Hughes, ―Programmable Logic Controller‖, ISA Publication.

7. Stuart A. Boyer, ―SCADA supervisory control and data acquisition‖, ISA Publication.

8. George Stephanopoulos, ―Chemical process control‖, PHI -1999

9. Paul Gruhn, Harry L cheddie, ― Safety Instrumented S ystem: Design, Analysis and

justification‖, ISA, 2nd edition, 2006.

10. Ian Verhappen, Augsto Periria, ―Foundation fieldbus‖, ISA,2006

## Page 35

Program Elective - III

Subject Code Subject Name Credits

INPE 2011 Electronics Systems Design 03

Course Objectives:

· To provide students with knowledge to design basic electronic systems.

· To make students aware of practical design considerations like noise reduction,

grounding techniques, shielding and isolation which are required to design high

performan ce electronic instrumentation systems.

Course Outcomes:

· Students will be able to understand practical design considerations such as Noise

reduction, Shielding and grounding techniques, Isolation and Power management

associated with design of electronic systems.

· Students will be able to design Analog, Digital and Mixed signal processing circuits

required for electronic systems.

Module Detailed content Hours

Prerequisite: Basic knowledge of analog and digital electronic circuits.

1 Design of linear integrated circuits and their applications: Linear and

log amplifiers, peak detect and milli volt rectifier circuits, analog

switches and multiplexers, current and voltages references and their

stability

06

2 Instrumentation and special operational amplifiers: Advanced

instrumentation amplifier and various designs to improve dynamic range

and reduce power dissipation. High speed OP -amps CMOS OP -amps

Micro power amplifiers low noise and chopper stabilized OP -amps

07

3 Nonlinear integrated circuits: Comparators, voltage to frequency and

frequency to voltage converters switched capacitor circuit ‘ s filters.

Analog filters, Sample and hold circuits.

06

4 Converters: D.C to D.C converters. Mixed signal processing. High

speed and high-resolution DACs and A/D converters. Various techniques

of A/D conversion. flash, successive approximation, multi slope ADC.

Delta sigma ADC.

08

## Page 36

5 Noise reduction techniques: Design of mixed signal processing circuits,

grounding and isolation techniques R.F shielding, Power supply noise

reduction and filtering, Over voltage and ESD protection.

08

6 Power Management : Power management issues in low power portable

systems, Linear and switch mode regulators. 04

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class test (on

minimum 02 Modules) and the other is either a class test or assignment on live problems or course

project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions

to be set each of 20 marks, out of these any four questions to be attempted by students.

Minimum 80% syllabus should be cov ered in question papers of end semester examination

References:

1. E.Allen Douglas R.Holberg, ―CMOS Analog Circuit Design‖, Philip Oxford ,

University Press 2004

2. Kevin M.Daugherty, ―Analog To Digital Converter‖, Tata McGraw Hill Inc 1995

3. Manual: Hig h Speed Design Technique - Analog Devices Inc 1996

4. Dan Shiengold, ―Non-Linear Integrated Circuits Handbook‖, Analog Devices.

5. Ralph Morrison,‖Grounding And Shielding Technique‖, Fourth Edition,John Wiley,1998

## Page 37

Subject Code Subject Name Credits

INPE2012 Advanced Fiber Optics and LASER Instrumentation 03

Course Objectives:

· To expose the students to the concepts of instrumentation based on optical

fibers and lasers along with their properties.

· To provide sufficient knowledge about the extensive utilization of optical

fibers and lasers in Industries.

Course Outcomes:

· Understand the principle of optical fibers, its losses, sources and detectors and their

importance.

· Understand the operation of lasers in detail.

· Master the various principles of optical fiber used for different parameter

measurement.

· Perceive the significance of the intensive use of laser and optical fiber in

Industrial applications.

Module Detail content Hours

Prerequisite: Awareness of light theory, Basics of fiber optics, Basics of

Physics of Laser, Basics of measurement in Instrumentation.

1 Optical Fibers and their properties: Ray theory, Principle of light

propagation through a fiber, different types of fibers and their properties,

Transmission characteristics of optical fiber, Absorption losses, Scattering

losses, Dispersion losses, Non -linear phenomena. 07

2 Optical sources and Detectors: LED, LD, PIN,

APD their characteristics, modulation circuits, optical detection

principle, LED coupling to fiber

05

3 Fiber Optic Sensors: Principle of fiber optic sensors, classification, principle

of intensity modulated sensors, phase modulated sensors, wavelength

modulated sensors, distributed optical fiber sensing

06

4 Optical Fiber Measurement: Measurement of numerical aperture, refractive

index profile, OTDR. concepts of temperature, flow, pressure and level

measurement.

08

## Page 38

5 Laser Fundamentals: Fundamental characteristics of lasers,3 and 4 level

lasers, its properties, modes, resonator configuration, Q switching and mode

locking. Types of lasers: solid, liquid and gas.

06

6 Industrial & Biomedical Application of Lasers: Laser for measurement of

distance, length velocity, acceleration, Material processing, Laser heating,

welding, melting and trimming of materials. Laser instruments for surgery,

Application of Laser for removal of tumors, brain surgery, oncology, plastic

surgery.

07

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class

test (on minimum 02 Modules) and the other is either a class test or assignment on live

problems or course project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions

to be set each of 20 marks, out of these any four questions to be attempted by students.

Minimum 80% syllabus should be covered in question papers of end semester examination.

References:

1. Gerd Keiser, ―Optical Fiber Communication‖, McGraw Hill

2. John M Senior, ―Optical Fiber Communications Principles and Practice‖,3rd edition, Pearson

3. D.A.Krohn, ―Fiber Optic Sensors - fundamentals and applications ‖3rd edition, ISA

4. I. John and Harry, ―Industrial lasers and their applications‖, McGraw Hill

5. John Crisp, ―Introduction to Fibre Optics‖, an imprint of Elseveir Science,1996

6. John F Ready, ―Industrial applications of Lasers, Academic Press,1978

## Page 39

Subject Code Subject Name Credits

INPE2013 Rehabilitation Engineering 04

Course Objectives:

● To develop an understanding of the principle and working of various rehabilitation aids.

● To give information about the application of various recent rehabilitation aids.

● To give information about rehabilitation medicine and Advocacy.

Course Outcomes:

● The students will be able to understand the principle and working of various

rehabilitation aids.

● The students will be able to understand the design considerations of various

rehabilitation aids.

● The students would be able to select which rehabilitation aid to apply for challenged

people based on their medical conditions.

● The student would be aware of the various legal considerations while selecting a

rehabilitation aid.

Module Detailed content Hours

Prerequisite: Knowledge of Anatomy and Physiology of Human Systems,

Knowledge of various basic stimulation techniques, Knowledge of basic

concept of human -assist devices.

1 Prosthetic and orthotic devices: Hand and arm replacement, different types of

models for externally powered limb prosthetics, feedback in orthotic system,

material for prosthetic and orthotic devices, mobility aids.

08

2 Auditory and speech assist devices: Types of deafness, hearing aids,

application of DSP in hearing aids, cochlear implants 05

3 Visual aids: Retinal Implants, Types of retinal implants – Epi-retinal and

subretinal, design and working, applications of retinal implants. Ultrasonic

and laser canes, Intraocular lens, Text voice converter, screen readers.

08

4 Medical stimulator: Muscle and nerve stimulator, Location for

Stimulation,Functional Electrical Stimulation, Sensory Assist Devices. 08

5 Rehabilitation medicine: Physiological aspects of Function

recovery, psychological aspects of Rehabilitation therapy. 06

## Page 40

6 Advocacy: Legal aspect available in choosing the device and provision

available in education, job and in day -to-day life. 04

Assessment:

Internal: Assessment consists of two tests out of which; one should be compulsory class test (on

minimum 02 Modules) and the other is either a class test or assignment on live problems or course

project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions to be

set each of 20 marks, out of these any four q uestions to be attempted by students. Minimum 80% syllabus

should be covered in question papers of end semester examination.

References:

1. Rory A Cooper, ―An Introduction to Rehabilitation Engineering‖, CRC press, 2006.

2. Joseph D.Bronzino, ―The Biomedic al Engineering Handbook‖,Third Edition,CRC

Press,2006

3. Levine.S.N.Editor, ―Advances in Bio Medical Engineering and Medical Physics‖,

Inter University Publication, New York 1968.

4. Albert M.Cook and Webster J.G, ―Therapeutic Medical devices‖, Prentice Ha ll Inc.,

New Jersey, 1982.

5. Reswick.J, ―What is Rehabilitation Engineering, Annual review of Rehabilitation -

volume2‖, Springer -Verlag, New York 1982.

## Page 41

Program Elective -IV

Subject Code Subject Name Credits

INPE2021 Advanced Nuclear Instrumentation 03

Course Objectives:

· To give students knowledge in the field of nuclear instrumentation, which is used for

various hi -tech applications including field of nuclear research, nuclear reactors,

accelerators and nuclear medical instruments

Course Outcomes:

· The students should be able to understand the design and working of

advanced nuclear instruments used in nuclear research, nuclear reactors

and other related nuclear fields.

· Students will be able to apply the concepts for basic design of nucl ear instruments.

Module Detailed content Hours

Prerequisite: Basic concepts of Radioactivity, Measurement

of Radioactivity.

1 Nuclear instrumentation for research: Radiation detectors for high

resolution nuclear pulse spectroscopy, HPGE, Ge(Li), Si(Li) detectors, high

resolution Multi Channel Analyzers, Nuclear ADCs, Wilkinson, Gatti‘s

sliding scale technique, various modes of Multi -Channel Analyzer, portable

spectro scopy systems and their design. Timing spectroscopy, Time Pick -off

circuits, TDCs, TACs, spectrum stabilization.

12

2 Instrumentation for reactors: Log and linear amplifiers, in core and out of

core instrumentation, Neutron detector, BF3 detector, Fission counters,

nuclear instrumentation for pressurized water reactors, boiling water

reactors, self -powered detectors, fast Neutron detection and spectroscopy.

08

3 Detection of very low radio -activity: Liquid scintillation counting

systems, noise reduction by coincidence detection. Counting interferences in

LSC, Methods of quench corrections.

03

4 Instrumentation for accelerators: Various types of accelerators,

detectors and electronics used. 03

## Page 42

5 Nuclear medical instrumentation: Functional imaging, design and

construction of imaging systems gamma camera, PET SPET. Calibrations

and testing of various nuclear instruments and systems.

10

6 Instrumentation for astrophysics experiments: Detection of cosmic

events, detector arrays and trigger systems 03

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class

test (on minimum 02 Modules) and the other is either a class test or assignment on live problems

or course project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions

to be set each of 20 marks, out of these any four questions to be attempted by students.

Minimum 80% syllabus should be covered in question papers of end semest er examination.

References:

1. G.F.Knoll ,―R adiation detection and measurement‖, John Wiely and Sons, 4th edition, 2010.

2. P.W. Nicolson, ―Nuclear electronics‖, John Wiely,1998.

3. Gerald. J.Hine, James A Sorenson, ―Instrumentation in nuclear Medicine‖, Vol II,

Academic press,1974

4. Ramesh Chandra, ―Nuclear Medicine Physics‖, Williams and Wilkins,1998.

5. Irving Kaplan ―Nuclear Physics.‖, Narosa Publishing House.1992

## Page 43

Subject Code Subject Name Credits

INPE2022 Machine Learning and Deep Learning 03

Course Objectives:

To give students knowledge in the field of Machine learning and Deep learning, which

find extensive applications in various fields, ranging from predictive analytics,

medical diagnosis, image processing, control engineering.

Course Outcomes: Students would be able

● To explain the basic concepts and techniques of Machine Learning.

● To have a thorough understanding of the Supervised and Unsupervised learning techniques

● To study the various probability -based learning technique s

● To understand the concepts of deep learning

Module Detailed content Hours

Prerequisite: Basic concepts of Expert systems and artificial intelligence

1 Introduction: Types of Machine Learning, Supervised Learning: concept of

working of brain and the neuron, Perspectives and Issues in Machine Learning,

Linear Discriminants – Perceptron – Linear Separability – Linear Regression

08

2 Linear models: Multi -layer Perceptron, Propagating Forwards, Propagating

Backwards: Back Propagation Error – Multi -layer Perceptron in Practice –

Examples of using the MLP – Overview – Deriving Back -Propagation – Radial

Basis Functions and Splines, Concepts of RBF Network.

06

3 Tree and Random Forest model: Decision Trees, Constructing Decision

Trees, Classification and Regression Trees, Ensemble Learning, Boosting,

Bagging, Different ways to Combine Classifiers, Random Forest algorithm

06

4 Probabilistic Model: Probability and Learning, Basic Statistics, Gaussian

Mixture Models, Nearest Neighbor Methods (kNN), Unsupervised Learning –

Clustering, K means Algorithm, Vector Quantization. 06

5 Dimensionality Reduction: Linear Discriminant Analysis, Principal

Component Analysis, Factor Analysis, Independent Component Analysis, 06

## Page 44

Locally Linear Embedding, Least Squares Optimization, Genetic algorithms

6 Deep learning: Basic concept of Deep learning, Optimization in deep

learning, non -convex optimization for deep networks, Stocha stic Optimization,

Generalization in neural networks, Recurrent networks, LSTM, Recurrent

Neural Network Language Models 07

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class

test (on minimum 02 Modules) and the other is either a class test or assignment on live problems

or course project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions to be

set each of 20 marks, out of these any four questions to be attemp ted by students. Minimum 80% syllabus

should be covered in question papers of end semester examination.

References:

1. Peter Flach, “Machine Learning: The Art and Science of Algorithms that Make Sense of Data”,

First Edition, Cambridge University Press, 2012

2. Ethem Alpaydin, “Introduction to Machine Learning 3e (Adaptive Computation and Machine

Learning Series)”, Third Edition, MIT Press, 2014

3. Jason Bell, “Machine learning – Hands on for Developers and Technical Professionals”, First

Edition, Wiley, 2014.

4. Tom M Mitchell, “Machine Learning”, First Edition, McGraw Hill Education, 2013.

5. Stephen Marsland, “Machine Learning – An Algorithmic Perspective”, Second Edition, Chapman

and Hall/CRC Machine Learning and Pattern Recognition Series, 2014.

## Page 45

Subject Code Subject Name Credits

INPE2023 MEMS and Nanotechnology 03

Course Objectives:

● To give students adequate knowledge regarding quantum mechanics to understand

principles utilized in Nanotechnology and MEMS.

● To familiarize the students with advanced technologies used in fabrication of nano

materials and MEMS.

Course Outcomes:

● Students will be able to understand concepts in quantum mechanics used in nanotechnology

● Students will be able to understand technologie s used in fabrication of nano materials

and MEMS.

Module Detailed content Hours

Prerequisite: Basic knowledge in quantum mechanics and material science.

1 Introduction: Introduction to nanotechnology and Nanomaterials, How It All

Began: Synthesis of carbon buckyballs, List of stable carbon allotropes

extended, fullerenes, metallofullerenes, solid C 60, bucky onions, nanotubes,

nanocones. 04

2 Quantum Mechanics : Review of classical mechanics, de Broglie's hypothesis,

Heisenberg uncertainty principle Pauli Exclusion Principle, Schrödinger's

equation, Properties of the wave function, Application: quantum well, wire, dot,

quantum cryptography Solid State Physics and Nanodevices -Structure and

bonding, Application: carbon nanotube, Electronic band structure Electron

statistics, Application: Optical transitions in solids, Semiconductor quantum

dots, photonic crystals. 10

3 Nanomaterials - Fabrication, MEMS and NEMS nanotubes synthesis:

Bottom -up vs. top -down approach, Epitaxial growth, Self -assembly, Modeling

and Applications Production Techniques of Nanotubes Carbon arc bulk

synthesis in presence and absence of catalysts Hi gh-purity material (Bucky

paper) production using Pulsed Laser Vaporization (PLV) of pure and doped

graphite High -pressure CO conversion (HIPCO) nanotube synthesis based on

Boudoir Reaction Chemical Vapor Deposition (CVD). 06

4 Nanomaterials: Characterization and commercial processes of synthesis of

nonmaterial, Nanoclay, Nanoinroganic materials, Nanocarbon Tubes CNT,

Applications of nanomaterials in water treatment, polymers,atalysis etc 07

## Page 46

Structural, XRD, TEM, SEM, STM, AFM.

5 MEMS Technology: Introduction to Microelectromechanical Systems

(MEMS), Microsensors and Micro -actuators, Micromachining, System

modeling and Simulation, different types of MEMS sensors and actuators. 06

6 Micro Electromechanical Systems: MEMS: Micro -transducers Analysis,

Design and Fabrication, Microprocessor -Based Controllers and

Microelectronics , Micro -switches, Micro -actuators for Electromechanical

systems. 06

Assessment:

Internal: Assessment consists of two tests out of which; one should be a compulsory class

test (on minimum 02 Modules) and the other is either a class test or assignment on live problems

or course project.

End Semester Examination: Some guidelines for setting the question papers are as, six questions to be

set each of 20 ma rks, out of these any four questions to be attempted by students. Minimum 80% syllabus

should be covered in question papers of end semester examination.

References:

1. K. Eric Drexler, ―Nanosystems: Molecular Machinery, Manufacturing, and

Computation‖, 1992 .

2. Mark Ratner & Daniel Ratner, ―Nanotechnology: A Gentle Introduction to the Next Big

Idea‖, November 2002 Read reviews .

3. Nitaigour Premchand Mahalik, ―MEMS ‖, Tata McGraw Hill, New Delhi, 2007.

4. K. K. Appukuttan, ―Introduction to Mechatronics‖, Oxford Higher Education, 2003.

5. Nitaigour Premchand Mahalik, ―Mechatronics‖, Tata McGraw -Hill, 2003

## Page 47

Subject Code Subject Name Credits

INL201 Program Lab -II 01

Expt No. Title

1 Simulation of batch reactor control using PLC with GUI

2 Study of Ethernet network communication

3 Study of Modbus communication

4 Simulation of furnace control using PLC with GUI

5 Simulation of Heat exchanger feedback control scheme using DCS

6 Simulation of cascade control scheme using DCS

7 Simulation of feedforward control scheme using DCS

8 Simulation of boiler level control using DCS

NOTE: Perform any six experiments from above list and two experiments from Department Elective

Course.

Term work: Term work consists of performing 08 practical mentioned above. Final certification and

acceptance of the term work ensures satisfactory performance of laboratory work

Assessment:

End Semester E xamination: Practical/Oral examination is to be conducted by a pair of internal and

external examiners.

## Page 48

Subject Code Subject Name Credits

INSBL201 Skill Based Lab -II 01

Expt. Title

1 Implement Linear Regression with example

2 Implement logistic regression with example

3 Implement Principal component analysis for dimensionality reduction

4 Implement Support Vector Machine with example

5 Implement Decision tree classification techniques

6 Implement Random Forest algorithm for an example

7 Implement clustering techniques with example

8 Implement any one deep learning algorithm for an example

NOTE: Perform any six experiments from above list and two experiments from Department Elective

Course.

Term work: Term work consists of performing 08 practicals mentioned above. Final certification and

acceptance of the term work ensures satisfactory performance of laboratory work

Assessment:

End Semester Examination: Practical/Oral examination is to be conducted by a pair of internal and

external examiners.

## Page 49

Semester III

Course

Code Course Name Teaching Scheme

(Contact Hours) Credits Assigned

Theory Pract. Tut. Theory Pract. Tut. Total

INMP301 Major Project:

Dissertation -I -- 20 -- -- 10 -- 10

Total 00 20 00 00 10 -- 10

Course

Code Course Name Examination Scheme

Theory Term

Work Pract/

Oral Total

Internal Assessment End

Sem

.

Exa

m Exam.

Durati

on (in

Hrs) Test-1 Test-2 Avg

INMP301 Major Project:

Dissertation -I -- -- -- -- -- 100 -- 100

Total -- -- -- -- -- 100 -- 100

Guidelines for Dissertation -I

Students should do a literature survey and identify the problem for Dissertation and finalize in consultation

with the Guide/Supervisor. Students should use multiple literatures and understand the problem. Students

should attempt to provide solutions to th e problem by analytical/simulation/experimental methods. The

solution to be validated with proper justification and compile the report in standard format. Guidelines for

Assessment of Dissertation -I.

Dissertation -I should be assessed based on following po ints

∙ Quality of Literature survey and Novelty in the problem

∙ Clarity of Problem definition and Feasibility of problem solution

∙ Relevance to the specialization

∙ Clarity of objective and scope Dissertation -I should be assessed through a present ation by a panel of Internal

examiners and external examiner appointed by the Head of the Department/Institute of respective

Programme.

## Page 50

Online Credit Courses

Course

Code Course Name Teaching Scheme

(Contact Hours) Credits Assigned

Theory Pract. Tut. Theory Pract. Tut. Total

XXOCC301 Online Credit Course - I -- -- -- -- -- -- 3

XXOCC301 Online Credit Course - II -- -- -- -- -- -- 3

Total -- -- -- 00 00 00 06

Note 2:

It is mandatory to complete the Online Credit Courses (OCC) available on NPTEL / Swayam

/MOOC or similar platform approved by UoM. These two courses shall be completed in any

semester I or II or III, but not later end of the Semester III. University shall make a provision that

credits earned with OCC - I and OCC -II shall be accounted in the third semester grade -sheet with

actual names of courses. The learner shall be allowed to take up these courses from his or her

institute or organisation/ industry where h is / her major project is carried out. The students shall

complete the courses and shall qualify the exam conducted by the respective authorities/ instructor

from the platform. The fees for any such courses and the corresponding examination shall be borne

by the learner.

Online Credit Course – I

The learner shall opt for the course in the domain of Research Methodology or Research & Publication

Ethics or IPR. The opted course shall be of 3 credits of equivalent number of weeks.

Online Credit Course –II

The learner shall opt for the course recommended by Faculty Advisor/ Project Supervisor from the

institute. The opted course shall be of 3 credits of equivalent number of weeks.

## Page 51

Semester IV

Course

Code Course Name Teaching Scheme

(Contact Hours) Credits Assigned

Theory Pract. Tut. Theory Pract. Tut. Total

INMP401 Major Project:

Dissertation -II -- 32 -- -- 16 -- 16

Total -- 32 -- -- 16 -- 16

Course

Code Course Name Examination Scheme

Theory Term

Work Pract/

Oral Total

Internal Assessment End

Sem

.

Exa

m Exam.

Durati

on (in

Hrs) Test-1 Test-2 Avg

INMP401 Major Project:

Dissertation -II -- -- -- -- -- 100 100 200

Total -- -- -- -- -- 100 100 200

Guidelines for Assessment of Dissertation II

Dissertation II should be assessed based on following points:

∙ Quality of Literature survey and Novelty in the problem

∙ Clarity of Problem definition and Feasibility of problem solution

∙ Relevance to the specialization or current Research / Industrial trends

∙ Clarity of objective and scope

∙ Quality of work attempted or learner contribution

∙ Validation of results

∙ Quality of Written and Oral Presentation

Students should publish at least one paper based on the work in the referred National/ International

conference/Journal of repute.

Dissertation II should be assessed by internal and External Examiners appointed by the University of

Mumbai.