ANNA UNIVTIRUNELVELI ME CONTROL@ INSTRU SYSLLABUS

ANNA UNIVERSITY:: CHENNAI – 600 025
M.E. CONTROL AND INSTRUMENTATION
CURRICULUM 2005 - FULL - TIME MODE

SEMESTER – I
Code No. Course Title L T P M
THEORY
MA1614 Applied Mathematics for Electrical Engineers
3 1 0 100
CI1601 Linear and Non-linear Systems Theory
3 0 0 100
CI1602 Digital Signal Processing
3 0 0 100
CI1603 Control System Design
3 1 0 100
CI1604 Transducers and Measurements
3 0 0 100
E1*** Elective I 3 0 0 100

SEMESTER - II
Code No. Course Title L T P M
THEORY
CI1651 Analog and Digital Instrumentation
3 1 0 100
CI1652 Digital Control System
3 0 0 100
CI1653 Process Control and Instrumentation
3 1 0 100
CI1654 Micro-Controller Based System Design
3 0 0 100
E2*** Elective II 3 0 0 100
E3*** Elective III 3 0 0 100
PRACTICAL
CI1655 Control and Instrumentation Lab
0 0 3 100

SEMESTER - III
Code No. Course Title L T P M
THEORY
E4*** Elective IV 3 0 0 100
E5*** Elective V 3 0 0 100
E6*** Elective VI 3 0 0 100
PRACTICAL
CI1751 Project Work Phase I 0 0 12 *

SEMESTER – IV
Code No. Course Title L T P M
PRACTICAL
CI1751 Project Work Phase II 0 0 24 *
* As per regulations 2005




LIST OF ELECTIVES
M.E. CONTROL AND INSTRUMENTATION

Code No. Course Title L T P M
CI1621 Robotics and Automation
3 0 0 100
CI1622 Advanced Topics in Instrumentation Systems
3 0 0 100
CI1623 Bio-Medical Instrumentation
3 0 0 100
CI1624 System Identification and Adaptive Control
3 0 0 100
CI1671 Computer Aided Analysis And Design Of Systems
3 1 0 100
CI1672 Digital Signal Processors
3 0 0 100
CI1673 Optimal Control and Filtering
3 0 0 100
PS1671 Intelligent Control
3 0 0 100





SEMESTER I

MA1614 APPLIED MATHEMATICS FOR ELECTRICAL ENGINEERS 3 1 0 100

1. ADVANCED MATRIX THEORY 9
Matrix norms – Jordan canonical form – Generalized eigenvectors – Singular value decomposition – Pseudo inverse – Least square approximations – QR algorithm.

2. CALCULUS OF VARIATIONS 9
Variation and its properties – Euler’s equation – Functional dependent on first and higher order derivatives – Functional dependent on functions of several independent variables – Some applications – Direct methods: Ritz and Kantorovich methods.

3. LINEAR PROGRAMMING 9
Basic concepts – Graphical and Simplex methods –Transportation problem – Assignment problem.

4. DYNAMIC PROGRAMMING 9
Elements of the dynamic programming model – optimality principle – Examples of dynamic programming models and their solutions.

5. RANDOM PROCESSES 9
Classification – Stationary random processes – Auto Correlation – Cross Correlations – Power spectral density – Linear system with random input – Gaussian Process.

L = 45 T = 15 TOTAL = 60
REFERENCES

1. Lewis.D.W., “Matrix Theory”, Allied Publishers,Chennai 1995.
2. Bronson,R, “Matrix Operations, Schaums Outline Series” ,McGraw Hill ,New York. 1989.
3. Elsgoltis, " Differential Equations and Calculus of Variations ", MIR Publishers, Moscow (1970).
4. Gupta.A.S., “Calculus of Variations with Applications”, Prentice Hall of
India,New Delhi,1999.
5. Taha, H.A., " Operations research - An Introduction ", Mac Millan publishing Co., (1982).
6. Gupta, P.K.and Hira, D.S., " Operations Research ", S.Chand & Co., New Delhi, (1999).
7. Ochi, M.K. " Applied Probability and Stochastic Processes ", John Wiley & Sons (1992).
8. Peebles Jr., P.Z., " Probability Random Variables and Random Signal Principles ", McGraw Hill Inc., (1993).




CI1601 LINEAR AND NON-LINEAR SYSTEMS THEORY 3 0 0 100
(Common for M.E. Power Systems Engineering, M.E. Power Electronics and Drives and M.E. Control & Instrumentation)

1. PHYSICAL SYSTEMS AND STATE ASSIGNMENT 9
Systems: Electrical - Mechanical – Hydraulic – Pneumatic – Thermal systems –Modelling of some typical systems like DC Machines - Inverted Pendulum.

2. STATE SPACE ANALYSIS 9
Realisation of State models: – Non-uniqueness - Minimal realization – Balanced realization – Solution of state equations: – State transition matrix and its properties - Free and forced responses – Properties: Controllability and observability- Stabilisability and detectability – Kalman decomposition.

3. MIMO SYSTEMS –FREQUENCY DOMAIN DESCRIPTIONS 9
Properties of transfer functions – Impulse response matrices – Poles and zeros of transfer function matrices – Critical frequencies – Resonance – Steady state and dynamic response – Bandwidth- Nyquist plots-Singular value analysis.

4. NON-LINEAR SYSTEMS 9
Types of non-linearity – Typical examples – Equivalent linearization - Phase plane analysis – Limit cycles – Describing functions- Analysis using Describing functions- Jump resonance.

5. STABILITY 9
Stability concepts – Equilibrium points – BIBO and asymptotic stability – Direct method of Liapunov – Application to non-linear problems – Frequency domain stability criteria – Popov’s method and its extensions.

L = 45 TOTAL = 45

REFERENCES
1. T.Glad and L.Ljung, “Control Theory – Multivariable and Non-linearmethods”, Taylor and Francis, London and NY.
2. M.Gopal, “Modern Control Engineering”, Wiley, 1996.
3. J.S. Bay, “Linear State Space Systems”, McGraw-Hill, 1999.
4. Eroni-Umez and Eroni, “System dynamics & Control”, Thomson Brooks/ Cole, 1998.
5. K. Ogatta, “Modern Control Engineering”, Pearson Education Asia, Low Priced Edition, 1997.
6. G.J.Thaler, “Automatic Control Systems”, Jaico publishers, 1993.



CI1602 DIGITAL SIGNAL PROCESSING 3 0 0 100

(Common for M.E. Power Systems Engineering, M.E. Control & Instrumentation, M.E. Power Electronics and Drives and M.E. Embedded System Technologies)

1. DISCRETE TIME SIGNALS AND SYSTEMS 9
Representation of discrete time signal – classifications – Discrete time – system – Basic operations on sequence – linear – Time invariant – causal – stable – solution to difference equation – convolution sum – correlation – Discrete time Fourier series – Discrete time Fourier transform.

2. FOURIER AND STRUCTURE REALIZATION 9
Discrete Fourier transform – properties – Fast Fourier transform – Z-transform – structure realization – Direct form – lattice structure for FIR filter – Lattice structure for IIR Filter.

3.FILTERS 9
FIR Filter – windowing technique – optimum equiripple linear phase FIR filter – IIR filter – Bilinear transformation technique – impulse invariance method – Butterworth filter – Tchebyshev filter.

4.MULTISTAGE REPRESENTATION 9
Sampling of band pass signal – antialiasing filter – Decimation by a n integer factor – interpolation by an integer factor – sampling rate conversion – implementation of digital filter banks – sub-band coding – Quadrature mirror filter – A/D conversion – Quantization – coding – D/A conversion – Introduction to wavelets.

5.DIGITAL SIGNAL PROCESSORS 9
Fundamentals of fixed point DSP architecture – Fixed point number representation and computation – Fundamentals of floating point DSP architecture – floating point number representation and computation – study of TMS 320 C 50 processor – Basic programming – addition – subtraction – multiplication – convolution – correlation – study of TMS 320 C 54 processor – Basic programming – addition – subtraction – multiplication – convolution – correlation.
L = 45 Total = 45

REFERENCES
1. John G.Proakis, Dimitris G.Manolakis, “Digital Signal Processing: Principles,
Algorithms and Applications”, PHI.
2. S.Salivahanan, A.Vallavaraj and C.Gnanapriya “Digital Signal Processing, TMH,
2000.
3. A.V. Oppenheim and R.W.Schafer, Englewood “Digital Signal Processing”, Prentice-
Hall, Inc, 1975.
4. Rabiner and Gold, “Theory and Application of Digital Signal Processing, A
comprehensive, Industrial – Strength DSP reference book.
5. B.Venkatramani & M.Bhaskar, “Digital Signal Processors architecture, programming
and applications”, TMH, 2002.




CI1603 CONTROL SYSTEM DESIGN 3 1 0 100

1. INTRODUCTION TO DESIGN AND CLASSICAL PID CONTROL 9
Systems performance and specifications –Proportional, Integral and Derivative Controllers – Structure – Empirical tuning- Zeigler Nichols-Cohen Coon – Root Locus method – Open loop inversion- affine parameterisation – Tuning using ISE, IAE and other performance indices .

2. CLASSICAL APPROACH AND COMPENSATOR DESIGN 9
Design of lag, lead, lead-lag compensators – Design using bode plots – Polar plots – Nichols charts – root locus and Routh Herwitz criterion.

3. STATE VARIABLE DESIGN 9
Design by state feedback – Output feedback – Pole assignment technique – Design of state and output feedback controllers – Design of reduced and full order observers – PI feedback – Dynamic state feedback.

4. OPTIMAL CONTROLLER DESIGN 9 Statement of optimal control problem – Solution using variational approach – Ricatti equation – Solution – Infinite time problems – Solution- Introduction to robust control - H∞ and H2 optimal control .

5. CASE STUDIES 9
Satellite altitude control – Lateral and Longitudinal control of Boeing 747, Control of Fuel-Air ratio in Automotive engine – Control of a digital tape transport – Control of Read/Write Head assembly of a Hard disk.

L = 45 T=15 TOTAL = 60

REFERENCES
1. G. C. Goodwin and etal, “ Control system design’, Pearson Education, 2003.
2. G. F. Franklin and etal, “ Feedback Control of Dynamic Systems”, Pearson Education systems, 2002.
3. John S. Bay, “ Linear State Space Systems”, MacGrawHill International edition, 1999.
4. M.Gopal, “Control Systems Principles and Design”, Tata MacGrawHill, New Delhi, 1998
5. W. J. Granttham, T.L. Vincent, “ Modern Control Systems Analysis and Design, John Wiley & Sons, 1993.




CI604 TRANSDUCERS AND MEASUREMENTS 3 0 0 100

1. BASIC TRANSDUCERS 9

Classification of transducers – Potentiometers – Differential transformers – Resistance strain gauges – Capacitance sensors – Eddy current sensors – Piezoelectric sensors - Photo-electric sensors – Resistance temperature detectors – Thermistors – Thermocouples – Elastic elements – Hall effect sensors – Electro dynamic sensors – Nuclear radiation sensors – Ultra sonic sensors – Smart sensors – Fibre optic sensors – Semiconductor IC sensors.

2. SMART SENSORS AND RECENT TRENDS IN SENSOR TECHNOLOGIES
9
Primary sensors, filters, converter – compensation – Non-linearity- Noise and interference – Drift – Information coding – Data coding – Data Communication – Standards for smart sensor interface – Film sensors – Semiconductor IC technology – MEMS – Nano sensors

3. SEMICONDUCTOR AND IC SENSORS 9

Requirements on Sensor Diodes – Applications of sensor diodes - Characteristics - Manufacturing techniques – Silicon temperature sensors – AD 7414 – Magnetic Field Sensors – AD 22151 – Photo Diodes - Optical sensors – Opto semiconductors – Industrial Auto sensors - AD 22050 – Characteristics - Manufacturing techniques.

4. SPECIFIC MEASUREMENT TECHNIQUES 9
Position measurement: Synchros and resolvers – Shaft encoders – Proximity Detectors. Flow measurement: Differential pressure flowmeters – Turbine flowmeter – Hotwire anemometers – Injection Flow measurement. Level measurement: Pressure operated transducers – Ultrasonic methods – Nucleonic methods – Optical sensors – Spectroscopy – Flame failure devices – Force balance transducers.

5. SIGNAL CONDITIONING CIRCUITS 9
Oscillators and signal generators – High frequency amplifiers – Active filters – Analog Modulators – Conuters – Data Acquisition System Design – Analysis of noise - DAS case studies : Temperature, Force, Sound and Position measurement system.

L = 45 TOTAL = 45


REFERENCES
1. Jones, B.E., “Instrument Technology”, Vol.3 Butter worth and Co., Publishers, 1987.
2. Andrew Parr,” Industrial Control – Handbook,” Newnes Industrial press –New Delhi 1998
3. Ernest O. Doebelin, “Measurement Systems”, McGraw-Hill Publishing Co., 1990.
4. James Dally, W., “Instrumentation for Engineering Measurements”, John Wiley & sons, Inc., 1993.
5. Patranabis, D., “Sensors and Transducers”, Wheeler Publishing, 1997.
6. Jonathan W Valvano,”Embedded Microcomputer systems”, PHI.
7. Sze Simon,” Semiconductor sensors “ Alibris Publications




SEMESTER - II

CI1651 ANALOG AND DIGITAL INSTRUMENTATION 3 1 0 100

1. BASIC BLOCKS 9
Overview of A/D converter, types and characteristics-Understanding Data acquisition, A/D and S/H terms-passive support and Active support components-Single and Multi-slope, Low cost A/D conversion techniques, types-Electromechanical A/D converter.

2. DATA ACQUISITION SYSTEMS 9
Objective - Building blocks of Automation systems – Multi, Single channel Data Acquisition systems, PC based DAS, Data loggers- Sensors based computer data systems.

3. INTERFACING AND DATA TRANSMISSION 9
Data transmission systems- 8086 Microprocessor based system design - Peripheral Interfaces – Time Division Multiplexing (TDM) – Digital Modulation – Pulse Modulation – Pulse Code Format – Interface systems and standards – Communications.

4. PC BASED INSTRUMENTATION 9

Introduction - Evolution of signal Standard - HART Communication protocol -Communication modes - HART networks - control system interface - HART commands -HART field controller implementation - HART and the OSI model - Field bus –Introduction - General field bus architecture - Basic requirements of field bus standard -field bus topology - Interoperability – interchangeability - Instrumentation buses-Mod bus - GPIB - Network buses – Ethernet - TCP/IP protocols

5. CASE STUDIES 9
PC based industrial process measurements like flow, temperature, pressure and level – PC based instruments development system.
L = 45 T=15 TOTAL = 60

REFERENCES
1. Kevin M. Daugherty, “Analog – to – Digital conversion – A Practical Approach”, McGraw Hill International Editions, 1995
2. N. Mathivanan, “Microprocessors, PC Hardware and Interfacing”, Prentice – Hall of India Pvt. Ltd., 2003.
3. Krishna Kant “Computer- based Industrial Control” ,Prentice- Hall of India Pvt. Ltd., 1997
4. H S. Kalsi, “Electronic Instrumentation”, Technical Education Series (TES)/TMH, New Delhi.
5. Buchanan., “Computer busses”, Arnold,London,2000.





CI1652 DIGITAL CONTROL SYSTEM 3 0 0 100

1. INTRODUCTION 9
Sampling and holding – Sample and hold devices – D/A and A/D conversion – Reconstruction – Z transform – Inverse Z transform – Properties – Pulse transfer function and state variable approach – Review of controllability, observability.

2. DESIGN USING TRANSFORM TECHNIQUES 9
Methods of discretisation – Comparison – Direct design – Frequency response methods –

3. DESIGN USING STATE SPACE TECHNIQUES 9

State space design – Pole assignment – Optimal control – State estimation in the presence of noise – Effect of delays.

4. COMPUTER BASED CONTROL 9
Selection of processors – Mechanization of control algorithms – PID control laws predictor merits and demerits – Application to temperature control – Control of electric drives – Data communication for control.

5. QUANTIZATION EFFECTS AND SAMPLE RATE SELECTION 9

Analysis of round off error – Parameter round off – Limit cycles and dither – Sampling theorem limit – Time response and smoothness – Sensitivity to parameter variations – Measurement noise and antialising filter – Multirate sampling.

L = 45 TOTAL = 45

REFERENCES
1. Gopal.M., “Digital control Engineering “, Wiley Eastern Ltd.,1989.
2. G.F.Franklin, J.David Powell, Michael Workman, “Digital control of Dynamic Systems”, 3rd Edition, Addison Wesley, 2000.
3. Paul Katz, “Digital control using Microprocessors”, Prentice Hall, 1981.
4. Forsytheand.W.Goodall.R.N., “Digital Control”, McMillan,1991.
5. Chesmond, Wilson, Lepla, “Advanced Control System Technology”, Viva – low price edition, 1998.




CI1653 PROCESS CONTROL AND INSTRUMENTATION 3 1 0 100

1. PROCESS DYNAMICS 9
Introduction to process control-objective of modelling-models of industrial process-hydraulic tanks-fluid flow systems-mixing process-chemical reactions-thermal systems-heat exchangers and distillation column.

2. CONTROL ACTIONS AND CONTROLLER TUNING 9
Basic control actions-on/off, P, P+I, P+I+D, floating control-pneumatic and electronic controllers- controller tuning-time response and frequency response methods- non-linear controllers.

3. COMPLEX CONTROL TECHNIQUES 9
Feed forward-ratio-cascade-split range-inferential-predictive-adaptive and multivariable control.

4. PROGRAMMABLE LOGIC CONTROLLERS 9

Evolution of PLC – Sequential and Programmable controllers – Architecture – Programming of PLC – Relay logic and Ladder logic – Functional blocks – Communication Networks for PLC.

5. DISTRIBUTED CONTROL SYSTEM 9

Evolution of DCS – Architecture – Local control unit – Operator interface – Engineering interface – Display – Case studies in DCS.
L = 45 T = 15 TOTAL = 60
REFERENCES

1. George Stephanopolus, "Chemical Process Control", Prentice Hall India
2. Harriot P., “Process Control”, Tata McGraw-Hill, New Delhi, 1991.
3. Norman A Anderson,” Instrumentation for Process Measurement and Control” CRC Press LLC, Florida, 1998.
4. Dale E. Seborg, Thomas F Edgar, Duncan A Mellichamp, “Process dynamics and control”, Wiley John and Sons, 1989.
5. Marlin T.E., “Process Control”, Second Edition McGraw hill, New York, 2000.
6. Balchan J.G. and Mumme G., “Process Control Structures and Applications”, Van Nostrand Renhold Co., New York,1988.
7. Lucas M.P, “Distributed Control System”, Van Nostrand Reinhold Co. NY 1986
8. Pertrezeulla, “Programmable Controllers”, McGraw-Hill, 1989



CI1654 MICRO-CONTROLLER BASED SYSTEM DESIGN 3 0 0 100

1. 8051 ARCHITECTURE 9

Basic Organization – Timing Diagrams : Fetch And Execute Cycle) – Instruction Set: Basic Operations, Addressing Modes.

2. PERIPHERALS AND THEIR INTERFACING 9

Typical Bus Structure – Bus- Memory - Timing Characteristics - Extended Mode And Memory Interfacing - Polling - Interrupts- Serial Ports- Analog And Digital Interfaces.

3. COMPUTATION 9

Assembly Language- Simple Programs- Usage Of Timers- Generation Of PWM, Other Signals- Interfacing Basic I/O Devices

4. 8096 ARCHITECTURE 9

CPU Operation – Interrupt Structure – Timers – HSI / HSO - Analog Interface – Serial Ports- I/O Ports - Watchdog Timers.

5. CASE STUDY 9

Real Time Clock- DC Motor Speed Control- Generation Of Gating Signals For Converters And Inverters- Frequency Measurement – Temperature Control.


L = 45 TOTAL = 45
REFERENCES

1. John B. Peatman, "Design with micro - controllers", Mc-Graw Hill International Ltd, Singapore, 1989.
2. Intel manual on 16 bit embedded controllers, Santa Clara, 1991.
3. Myko Predko. “Programming and customizing the 8051 microcontroller”, Tata Mcgrawhill , 1999.
4. Muhammad Ali Mazidi, Janice Gillispie mazidi. “The 8051 Microcontroller and Embedded systems”, Pearson Education, 2004.
5. Michael Slater, " Microprocessor based design ", A Comprehensive guide to effective hardware design, Prentice Hall, New Jersey, 1989.




CI1655 CONTROL & INSTRUMENTATION LABORATORY 0 0 3 100

LIS OF EXPERIMENTS

1. Study of MATLAB, LABVIEW and MATHCAD on control applications.

2. Study of Data Loggers / Data Acquisition Systems.

3. Experimental modelling of Transducers

4. Simulation of Electric drives with P, PI and PID controllers using MATLAB /
MATHCAD

5. Interfacing PC with Real-time systems.

6. Digital position control system.

7. Digital control of second-order plan using Micro controllers.

8. Digital temperature and level control.

9. Design and analysis of second-order filters.

10. Design of DSP based controllers.

11. Design of Intelligent controllers for physical systems.

12. Design of Programmable Logic Controllers for real-time systems.

P= 45 Total = 45


PROJECT WORK (PHASE I) 0 0 12 *

* Refer clause P.G Regulation 2005, 4.4.4 on Project work.


PROJECT WORK (PHASE – II) 0 0 24 *




ELECTIVES

CI1621 ROBOTICS AND AUTOMATION 3 0 0 100

1. INTRODUCTION 8
Geometric configuration of robots – Manipulators – Drive systems – Internal and external sensors – End effectors – Control systems – Robot programming languages and applications – Introduction to robotic vision.

2. ROBOT ARM KINEMATICS 9
Direct and inverse kinematics – Rotation matrices – Composite rotation matrices – Euler angle representation – Homogenous transformation – Denavit Hattenberg representation and various arm configuration.

3. ROBOT ARM DYNAMICS 9
Lagrange – Euler formulation, joint velocities – Kinetic energy – Potential energy and motion equations – Generalised D’Alembert equations of motion.

4. PLANNING OF MANIPULATOR TRAJECTORIES 9
General consideration on trajectory planning joint interpolation & Cartesian path trajectories.

5. CONTROL OF ROBOT MANIPULATORS 10
PID control computed, torque technique – Near minimum time control – Variable structure control – Non-linear decoupled feedback control – Resolved motion control and adaptive control.
L = 45 TOTAL = 45

REFERENCES
1. Fu, K.S. Gonazlez, R.C. and Lee, C.S.G., “Robotics (Control, Sensing, Vision and Intelligence), McGraw-Hill, 1968 (II printing).
2. Wesley, E. Sryda, “Industrial Robots: Computer interfacing and Control” PHI, 1985.
3. Asada and Slotine, “Robot Analysis and Control”, John Wiley and Sons, 1986.
4. Philippe Coiffet, “Robot Technology” Vol. II (Modelling and Control), Prentice Hall INC, 1981.
5. Saeed B. Niku, “Introduction to Robotics, Analysis, systems and Applications”, Pearson Education, 2002
6. Groover M. P. Mitchell Wesis., “Industrial Robotics Technology Programming and Applications”, Tata McGraw-Hill, 1986.




CI1622 ADVANCED TOPICS IN INSTRUMENTATION SYSTEMS 3 0 0 100

1. FIBRE OPTIC INSTRUMENTATION 9

Fiber optics sensors - fiber optic instrumentation system -Different types of modulators – detectors - Interferometer method of measurement of length - moire fringes - measurement of pressure, temperature, current, voltage, liquid level and strain - fiber optic gyroscope-polarization maintaining.


2. LASER INSTRUMENTATION 9

Laser for measurement of distance, length, velocity, acceleration, current, voltage, atmospheric effect - material processing - laser heating, welding, melting and trimming of materials - removal and vaporization.

3. MICROPROCESSOR BASED INSTRUMENTATION 9

Hardware and firmware components of a microprocessor system - micro controllers - multiple processors - An example application of a microprocessor system -calibration and correction - human interface - computer interface - software characteristics of the computer interface - numerical issues - Embedded programming issues.

4. SMART INSTRUMENTS 9

Smart/intelligent transducer-comparison with conventional transducers-self diagnosis and remote Calibration features-Smart transmitter with HART communicator-Measurement of strain, flow, and pH with smart transmitters.

5.VIRTUAL INSTRUMENTATION 9
Block diagram and architecture of the virtual instrumentation - VIs and sub VIs, loops and charts, arrays, clusters and graphs, case and sequence structures, formula nodes, local and global variables, string and file I/O.
L = 45 TOTAL = 45
REFERENCES

1. Chapman,P., “Smart Sensors”, ISA Publications,1995.
2. John F Ready, “Industrial Applications of Lasers”, Academic press,1978.
3. Jasprit Singh, “Semiconductor Optoelectronics”, McGraw Hill, 1995.
4. F.Coombs, jr, Electronic instrument handbook Clyde. second edition
5. Lisa K.Wells & Jeffrey Travels, ‘ Labview for every one”, Prentice Hall, 1997
6. Sokoloff, “Basic concepts of Labview 4”, Prentice Hall 1998 .




CI1623 BIO MEDICAL INSTRUMENTATION 3 0 0 100

1. BASIC CONCEPTS OF BIO MEDICAL INSTRUMENTATION 6
Terminology – Generalised medical instrumentation system – Measurement constrains – Classification – Interfacing and modifying inputs – Bio statistics – Static and dynamic characteristic – Regulation of medical devices – Electrical safety in medical environment.

2. BASIC SENSORS AND SIGNAL PROCESSING 10
Displacement measurements – Resistive sensors – Bridge circuits – Inductance, capacitance and piezo electric sensor – Temperature measurements – Thermocouples – Radiation thermometry – Fibre optic temperature sensors – Optical measurements – Op-amp circuits – Phase sensitive demodulation – Oscillographic, galvanometric and potentiometric recorders – Microcomputers in bio medical instrumentation.

3. BIO POTENTIALS AND MEASUREMENTS 6
Electric activity and excitable cells – Functional organization of peripheral nervous system. ENG, EMG, ECG, EEG & MEG – Bio-potential electrodes – Electrolyte interface. Polarization – Body surface recording electrodes – Electrodes for electric simulation of tissues – Practical hints for using electrodes – Bio potential amplifiers.

4. BLOOD PRESSURE, FLOW AND SOUND MEASUREMENT 8
Direct and indirect blood pressure measurement and analysis – Bandwidth requirement – Typical waveforms – Phono-cardiography – Tonometry – Electro magnetic and ultrasonic flow meters – Photo plethysmography.

5. CLINICAL MEASUREMENT AND IMAGING SYSTEMS 15
Respiratory instruments – Transducers, spirometers, pulmonary measurements and instruments – Oxymeter – Laser application in medicines – Pulsed ruby, Nd Yag, Argon and Carbon-dioxide lasers – X-ray machines – Fluoroscopic machines, thermogram equipments – Ultrasonic imaging – Scanning methods and applications – Image evaluation and processing in medical field – Artificial assist devices.
L = 45, TOTAL = 45
REFERENCES
1. Khandpur R.S., “Handbook of Bio-medical Instrumentation”, Tata McGraw-Hill Publication Company, 1989.
2. Dean D.E. Marre A., “Bio electronic Measurements”, Prentice Hall, 1983.
3. All Evans, “ The Evaluation of Medical Images”, Adam Hilger publication, 1981.
4. John G.Webster, “Medical Instrumentation Application and Design”, John Wiley and Sons, 1999.
5. Cromwell. L.Fred J.Webbell, “Bio medical Instrumentation and Measurements”, Prentice Hall, 1995.




PS1671 INTELLIGENT CONTROL 3 0 0 100

1. INTRODUCTION 9

Approaches to intelligent control. Architecture for intelligent control. Symbolic reasoning system, rule-based systems, the AI approach. Knowledge representation. Expert systems.

2.ARTIFICIAL NEURAL NETWORKS 9
Concept of Artificial Neural Networks and its basic mathematical model, McCulloch-Pitts neuron model, simple perceptron, Adaline and Madaline, Feed-forward Multilayer Perceptron. Learning and Training the neural network. Data Processing: Scaling, Fourier transformation, principal-component analysis and wavelet transformations. Hopfield network, Self-organizing network and Recurrent network. Neural Network based controller

3. GENETIC ALGORITHM 9
Basic concept of Genetic algorithm and detail algorithmic steps, adjustment of free parameters. Solution of typical control problems using genetic algorithm. Concept on some other search techniques like tabu search and ant-colony search techniques for solving optimization problems.

4. FUZZY LOGIC SYSTEM 9
Introduction to crisp sets and fuzzy sets, basic fuzzy set operation and approximate reasoning. Introduction to fuzzy logic modeling and control. Fuzzification, inferencing and defuzzification. Fuzzy knowledge and rule bases. Fuzzy modeling and control schemes for nonlinear systems. Self-organizing fuzzy logic control. Fuzzy logic control for nonlinear time-delay system.

5. APPLICATIONS 9
GA application to power system optimisation problem, Case studies: Identification and control of linear and nonlinear dynamic systems using Matlab-Neural Network toolbox.
Stability analysis of Neural-Network interconnection systems. Implementation of fuzzy logic controller using Matlab fuzzy-logic toolbox. Stability analysis of fuzzy control systems.
L=45 T=45




REFERENCES
1. Jacek.M.Zurada, "Introduction to Artificial Neural Systems", Jaico Publishing House, 1999.
2. KOSKO,B. "Neural Networks And Fuzzy Systems", Prentice-Hall of India Pvt. Ltd., 1994.
3. KLIR G.J. & FOLGER T.A. "Fuzzy sets, uncertainty and Information", Prentice-Hall of India Pvt. Ltd., 1993.
4. Zimmerman H.J. "Fuzzy set theory-and its Applications"-Kluwer Academic Publishers, 1994.
5. Driankov, Hellendroon, "Introduction to Fuzzy Control", Narosa Publishers.




CI1624 SYSTEM IDENTIFICATION AND ADAPTIVE CONTROL 3 0 0 100

1. SYSTEMS AND MODELS 9
Models of LTI systems: Linear Models-State space Models, Model sets, Structures and Identifiability-Models for Time-varying and Non-linear systems: Models with Nonlinearities – Non-linear state-space models-Black box models, Fuzzy models, Model approximation and validation-Random Process Modelling.

2. PARAMETRIC AND NON-PARAMETRIC ESTIMATION METHODS 9
Transient response and Correlation Analysis – Frequency response analysis – Spectral Analysis – Least Square – Recursive Least Square –Maximum Likelihood – Instrumental Variable methods – Pseudo Linear Regression

3. LINEAR AND NON-LINEAR ESTIMATION TECHNIQUES 9
Open and Closed loop identification: Approaches – Direct and indirect identification – Joint input-output identification – Non-linear system identification – Wiener models – Power series expansions - Multidimensional Identification – State estimation techniques – FFT based, Model based Spectral estimation techniques.

4. CLASSIFICATION OF ADAPTIVE CONTROL 9
Introduction – Uses – Auto tuning – Self Tuning Regulators (STR) – Model Reference Adaptive Control (MRAC) – Types of STR and MRAC – Different approaches to self-tuning regulators – Stochastic Adaptive control – Gain Scheduling.

5. APPLICATIONS OF ADAPTIVE CONTROL 9

Recent trends in self – tuning – Stability, Convergence and Robustness studies - Model Updating – General purpose Adaptive regulator – Applications to process control.
L = 45 TOTAL = 45

REFERENCES
1. Ljung,” System Identification Theory for the User”, PHI, 1987.
2. Rolf Johansson,” System Modelling and Identification”, Prentice Hall of India,
3. Astrom and Wittenmark,” Adaptive Control ”, PHI
4. William S. Levine, “ Control Hand Book”.
5. Narendra and Annasamy,” Stable Adaptive Control Systems, Prentice Hall, 1989.





CI1671 COMPUTER AIDED ANALYSIS AND DESIGN OF SYSTEMS
3 1 0 100

1. ALGORITHM FOR SYSTEM SIMULATION 9
Linear and Non linear equation – solution – computation algorithm – transfer function and state space model – realization – simulation – properties

2. CONTROLLER DESIGN 9

Algorithms for developing Bode – Nyquist – polar plots- optimisation – controller design – system performance evaluation


3. SIMULATION OF PHYSICAL SYSTEMS 9
Simulation of Electrical – Mechanical – Hydraulic – Thermal – Process systems

4. CLOSED LOOP OPERATION 9

Design of controllers – sensor dynamics – noise generation – closed loop simulation

5. SYMBOLIC PROGRAMMING 9
Introduction- Symbolic programming – programming constructs – data structure – computation with formulae - procedures – numerical programming

L = 15 T=15 P=60
REFERENCES
1. Chen, ”System and signal analysis”, second edition , oxford university press, 1994.
2. K. Ogatta ,” Modern control Engineering “, Fourth edition ,Pearson education 2002
3. Dorf and Bishop ,” Modern control engineering”, Addison Wesley, 1998
4. MAPLE V programming guide
5. MATLAB/ SIMULINK user manual
6. MATHCAD / VIS SIM user manual






CI1672 DIGITAL SIGNAL PROCESSORS 3 0 0 100

1. INTRODUCTION 9
Algorithms for signal processing – Basic architecture of DSPs.

2. TEXAS PROCESSORS 9
Architecture – Addressing modes – Instruction set – Programming

3. PERIPHERALS INTERFACES OF DSP 9
Peripherals – memory – Applications.

4. EXTERNAL INTERFACE 9
Digital and analog Interface – Host interface – Memory interface – DMA ports – Serial ports.

5. SPECIAL PROCESSORS FOR MOTOR CONTROL 9
Architecture – Special features – PWM generation – controller implementation
L=45 TOTAL = 45

REFERENCES

1. K.Padmanabhan et al. “A Practical approach to Digital Signal Processing “, New Age Publications, 2001
2.B. Venkataramani et al. “Digital Signal Processor – Architecture, Programming and Applications , TMH, New Delhi 2002.
3. Texas Instruments – Manuals.





CI1673 OPTIMAL CONTROL AND FILTERING 3 0 0 100

1. INTRODUCTION 8
Statement of optimal control problem – Problem formulation and forms of optimal control – Selection of performance measures. Necessary conditions for optimal control – Pontryagin’s minimum principle – State inequality constraints – Minimum time problem.

2. LQ CONTROL PROBLEMS AND DYNAMIC PROGRAMMING 10
Linear optimal regulator problem – Matrix Riccatti equation and solution method – Choice of weighting matrices – Steady state properties of optimal regulator – Linear tracking problem – LQG problem – Computational procedure for solving optimal control problems – Characteristics of dynamic programming solution – Dynamic programming application to discrete and continuous systems – Hamilton Jacobi Bellman equation.

3. NUMERICAL TECHNIQUES FOR OPTIMAL CONTROL 8
Numerical solution of 2-point boundary value problem by steepest descent and Fletcher Powell method solution of Ricatti equation by negative exponential and interactive methods

4. FILTERING AND ESTIMATION 9
Filtering – Linear system and estimation – System noise smoothing and prediction – Gauss Markov discrete time model – Estimation criteria – Minimum variance estimation – Least square estimation – Recursive estimation.

5. KALMAN FILTER AND PROPERTIES 10
Filter problem and properties – Linear estimator property of Kalman Filter – Time invariance and asymptotic stability of filters – Time filtered estimates and signal to noise ratio improvement – Extended Kalman filter.

L = 45, TOTAL = 45
REFERENCES
1. Krik D.E., “Optimal Control Theory – An introduction”, Prentice hall, N.J., 1970.
2. Sage, A.P., “Optimum System Control”, Prentice Hall N.H., 1968.
3. Anderson, BD.O. and Moore J.B., “Optimal Filtering”, Prentice hall Inc., N.J., 1979.
4. S.M. Bozic, “Digital and Kalman Filtering”, Edward Arnould, London, 1979.
5. Astrom, K.J., “Introduction to Stochastic Control Theory”, Academic Press, Inc, N.Y., 1970.