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ME CONTROL SYSTEMS (Min
imum credits to be earned: 75)
Course Code
Course TitleHours/Week
CreditsMaximum Marks
Lecture Tutorial Practical CA FE Total
CORE THEORY COURSES
09EC01Linear Algebra and Optimization Techniques
3 - - 3 50 50 100
09EC02 Modelling and Simulation 3 - - 3 50 50 100
09EC03 Linear Systems 3 - - 3 50 50 100
09EC04 Advanced Digital Signal Processing 3 - - 3 50 50 100
09EC05 PC Based Instrumentation 3 - - 3 50 50 100
09EC06 Industrial Drives and Control 3 - - 3 50 50 100
09EC07 Non Linear Control 3 - - 3 50 50 100
09EC08 Control Systems Design 3 - - 3 50 50 100
09EC09 Process Control 3 - - 3 50 50 100
ELECTIVE THEORY COURSES ( Six to be opted- out of which two may be opted from other programmes)
09EC11 Robust Control 3 - - 3 50 50 100
09EC12 Optimal Control System 3 - - 3 50 50 100
09EC13 Adaptive Control System 3 - - 3 50 50 100
09EC14 Logic and Distributed Control System
3 - - 3 50 50 100
09EC15 Robotics and Automation 3 - - 3 50 50 100
09EC16State Estimation and Parameter Identification
3 - - 3 50 50 100
09EC17 Introduction to MEMS 3 - - 3 50 50 100
09EC18 Industrial Data Networks 3 - - 3 50 50 100
09EC19 Embedded Systems 3 - - 3 50 50 100
09EC20 Intelligent Controllers 3 - - 3 50 50 100
SEMINAR
09EC41 Industrial Visit & Technical Seminar 1 - 2 2 100 - 100
PRACTICALS
09EC51 Process Control Laboratory - - 3 2 100 - 100
09EC52 Industrial Automation Laboratory - - 3 2 100 - 100
09EC55Object Computing and Data Structures Laboratory
2 - 3 4 100 - 100
PROJECT WORK
09EC71 Project Work - I - - 12 6 100 - 100
09EC72 Project Work - II - - 28 14 50 50 100
165
09EC01 LINEAR ALGEBRA AND OPTMIZATION TECHNIQUES3 0 0 3
VECTOR SPACES: Definition and examples, Subspaces, Linear independence, Basis, Dimension of a vector space. Linear transformation – Matrix as a linear transformation, Linear Operators - Null space and Range – Examples – Rank and Nullity – Operator inverses – Application to Matrix Theory – Computation of Range and Null Space of a Matrix – Matrix Operators – Operator Algebra – Change of Basis and similar Matrices.
(10) INNER PRODUCT SPACES: Definition and examples – Norm: Angle between vectors –Orthogonal bases, Gram-Schmdit process, QR decomposition – Best approximation and Least squares – Orthogonal matrices.
(10)
LPP : Simplex method – Two Phase method – Revised Simplex Method – Karmarker’s Algorithm . (5)
NON LINEAR PROGRAMMING: Introduction – Interval halving method – Fibonacci method – Univariate method- Pattern search method – Hookes and Jeeves method – Gradient of a function – Steepest descent method – Conjugate gradient method- Fletcher – Reeves method.
(7)
DYNAMIC PROGRAMMING: Principle of Optimality – Backward and forward induction methods - Calculus method of solution - Tabular method of solution – Shortest path network problems – Applications in production.
(5)
DECISION MAKING : Decisions under uncertainty, under certainty and under risk-Decision trees – Expected value of perfect information and imperfect information.
(5)
Total 42
REFERENCES:1. Howard Anton, “Elementary Linear Algebra with Applications”, John Wiley, 2005.2. David C Lay, “Linear Algebra and its Applications”, Addition Wesley, 2003.3. Hamdy A Taha, “Operations Research – An Introduction”, Prentice Hall, 2006.4. Singiresu S Rao, “Engineering Optimization Theory and Practice”, New Age International, 2006.
09EC02 MODELLING AND SIMULATION3 0 0 3
INTRODUCTION: Introduction to modeling, a systematic approach to model building, classification of models. Components of a system - Continuous and discrete systems.
(7)
RANDOM NUMBER GENERATION: Mid-square method - Constant multiplier method - Additive congruential method - Linear congruential method - Test for random numbers: Chi-square test - Kolmogorov-Smirnov Test - Runs test - Gaps test. (8)
RANDOM VARIABLE GENERATION: Inverse transform technique - Exponential distribution - Poisson distribution - Uniform distribution - Weibull distribution - Empirical distribution - Normal distribution - The Rejection method.
(9)
SIMULATION OF DISCRETE SYSTEMS: Solution strategies for lumped parameter models. Stiff differential equations. Solution methods for initial value and boundary value problems. Euler’s method. R-K method, shooting method, finite difference methods. Solving the problems using MATLAB.
(10) SIMULATION LANGUAGES: Simulation using C++/MATLAB/ LabVIEW-Control Design Tool Suit. Case Studies-CSTR, Steam Drum Control, Surge Vessel Level Control, Kiln Temperature Control . .
(8)
Total 42 REFERENCES:1. Jerry Banks, John S Carson II, Barry L Nelson and David M Nicol, "Discrete - Event System Simulation", Prentice Hall of India Ltd., New Delhi, Fourth Edition, 2004.2. Averill M Law and W. David Kelton, "Simulation, Modelling and Analysis", Tata McGraw Hill, Third Edition, 2003.3. Gottfried B S, "Elements of Stochastic Process Simulation", Prentice Hall, London, 1984.4. Narasingh Deo, "System Simulation using Digital Computer", Prentice Hall of India, 2003.5. Wayne Bequette W, "Process Control: Modelling, Design and Simulation", Prentice Hall of India, 2003.
09EC03 LINEAR SYSTEMS
166
3 0 0 3
MODERN CONTROL THEORY: Limitations of conventional control theory - Concepts of state, State variables and state model – state model for linear time invariant systems: State space representation using physical-Phase and canonical variables.
(8) SYSTEM RESPONSE: Transfer function from state model - Transfer matrix - Decomposition of transfer functions Direct, cascade and parallel decomposition techniques - Solution of state equation - State transition matrix computation. (9)
DISCRETE SYSTEM: State space representation of discrete system - Decomposition of Transfer functions - Solution of discrete time system - state transition matrix - Discretisation of continuous time state equations. (8)
SYSTEM MODELS: Characteristic equation - Eigen values and Eigen vectors - Invariance of Eigen values -Diagonalization - Jordan Canonical form - Concepts of controllability and observability - Kalman's and Gilbert's tests - Controllable and observable phase variable forms - Effect of pole-zero cancellation on controllability and observability.
(9)
LIAPUNOV STABILITY: Liapunov stability analysis - Stability in the sense of Liapunov - Definiteness of Scalar Functions – Quadratic forms - Second method of Liapunov - Liapunov stability analysis of linear time invariant systems.
(8)
Total 42REFERENCES:1. Katsuhiko Ogata, "Modern Control Engineering", Prentice Hall of India Private Ltd., New Delhi, Third Edition, 2002.2 Nagrath I J and Gopal M, "Control Systems Engineering", New Age International Publisher, New Delhi, 2006.3. Gopal M, “Digital Control and State Variable Methods”, Tata McGraw-Hill Publishing Company Limited, NewDelhi, India,
Second Edition, 2003.4. Nise S Norman, “Control Systems Engineering”, John Wiley & Sons, Inc, Delhi, Third edition, 2000.5. Benjamin C Kuo, “Automatic Control Systems”, John Wiley & Sons, Inc., Delhi, 2002.
09EC04 ADVANCED DIGITAL SIGNAL PROCESSING3 0 0 3
REVIEW OF DSP CONCEPTS: Signals – Classification of signals – LTI system-properties –convolution-overlap adds and overlap save, correlation. Review of FIR and IIR filter design – Discrete Fourier Transform – Fast Fourier Transform. (8)
MULTIRATE SIGNAL PROCESSING: Decimation- Interpolation – Multirate identities – Polyphase represenatations - Design of quadrature filter bank – PR condition- Application of filterbank in speech and image coding.
(8)
WAVELET TRANSFORM: Fourier Transform – Limitation of Fourier Transform – Short Time Fourier Transform – Continuous Wavelet Transform – Discrete Wavelet Transform – Implementation of Discrete Wavelet Transform through Lifting Scheme and Filter bank – Applications of wavelet transform in image fusion, image denoising and image compression.
(10)
DISCRETE-TIME RANDOM PROCESS: Random variables – Ensemble average – Gaussian random variables – Stationary processes – Wide sense Stationarity – Ergodicity – Types of random process – Auto regressive (AR), Moving Average (MA) and Autoregressive Moving Average Processes (ARMA).
(8)
SPECTRUM ESTIMATION: Nonparametric methods – The periodogram – Performance of the periodiogram – The Modified Periodiogram – Bartlett’s method – Welch Method – Blackman-Tukey method- Performance comparisons. (8)
Total 42
REFERENCES:1. Emmanuel C Ifeachor and Barrie W Jervis, “Digital Signal Processing – A Practical Approach,” Pearson Education, 2002.2. Raghuveer M Rao and Ajit S Bopardikar, “Wavelet Transforms, Introduction to Theory and Applications,” Pearson
Education, Asia, 2000.3. Fliege N J, “Multirate Digital Signal Processing,” John Wiley and Sons, 1994.4. Monson H Hayes, “Statistical Digital Signal Processing and Modeling,” John Wiley and Sons, 2006.
09EC05 PC BASED INSTRUMENTATION3 0 0 3
INTRODUCTION: Functional elements of a measurement system, General functional description of a digital system, Basic instrumentation components, Virtual instrumentation, Virtual instrument and traditional instrument, Hardware and software for
167
virtual instrumentation, Virtual instrumentation for test, control, and design, Graphical system design, Graphical programming and textual programming.
(8)
PROGRAMMING TECHNIQUES: Software environment, Data types, Data flow, VIs and sub VIs, Loops, Arrays, Clusters, Plotting data, Structures, Strings, file handling, local and global variables, State Machines, creating an executable application.
(9)
DATA ACQUISITION: DAQ system overview and configuration, Signal conditioning, DAQ hardware - Analog Input, Analog Output, Counters/Timers, Digital I/O, DAQ software, Grounding and shielding concepts, Instrument control - VISA.
(8)
INTERFACE STANDARDS AND PC BUSES: RS232, RS422, RS485, GPIB, USB, Firewire; Backplane buses - PCI, PCI-Express, PXI, PXI – Express, VME, VXI; Ethernet – TCP/IP protocols.
(8)
CONTROL APPLICATIONS: Machine Vision; Motion control; Remote Data Management – Data Sockets, Web Server; Data Logging and supervisory control; Toolboxes for specialized applications – System Identification toolkit, Control Design toolkit, Simulation Interface toolkit.
(9)
Total 42REFERENCES:1. Gary Johnson and Richard Jennings, “LabVIEW Graphical Programming”, McGraw Hill Inc., Fourth Edition, 2006.2. Lisa K Wells and Geffrey Travis, “LabVIEW for Everyone: Graphical Programming Even Made Easier”, Prentice Hall Inc.,
1996.3. William Buchanan, “Computer Buses Design and Application”, CRC Press, 2000.4. Sanjay Gupta and Joseph John, “Virtual Instrumentation using LabVIEW”, Tata McGraw-Hill Inc., 2005. 5. Clyde F Coombs, “Electronic Instruments Handbook”, McGraw Hill Inc., Third Edition, 1999.
09EC06 INDUSTRIAL DRIVES AND CONTROL3 0 0 3
CONVERTER FED DC DRIVES: Single-phase and Three-phase drives - Separately excited and series motor drives - Semi converter and full Converter drives - General analysis - Evaluation of performance parameters - Dual converter fed drives. (7) CHOPPER FED DC DRIVES: Single- quadrant chopper controlled drives -Evaluation of performance parameters for separately excited and series motor drives - Two quadrant and four quadrant chopper controlled drives.
(7)
INDUCTION MOTOR DRIVES: Stator Control: Stator voltage control of 3-Phase induction motors : - control by AC voltage controllers - Variable frequency square wave VSI drives - PWM Drives - CSI drives - closed loop control. (7)
ROTOR CONTROL AND VECTOR CONTROL: Static rotor resistance control - Slip power recovery : Static Kramer drive - Static Scherbius drive. Principle of vector control -Rotor flux - Oriented control, Stator Flux-oriented control, Magnetizing flux-oriented control of Induction machines - speed control of brushless DC motor drives. (10) SENSORLESS VECTOR AND DIRECT TORQUE CONTROLLED DRIVES AND SPECIAL DRIVES: Basic types of torque controlled drive scheme: vector drives- direct torque controlled drives. Synchronous Motor Drives: Scalar control – self control modes - Permanent magnet motor control - Switched reluctance motor and stepper motor drives. (11)
Total 42
REFERENCES:1. Gopal K Dubey, “Fundamentals of Electric Drives”, Narosa Publishing House, New Delhi, 2005.2. Ion Boldea and Nasar S A, “Electric Drives”, CRC Press LLC, New York, 1999.3. Pillai S K, “Analysis of Thyristor Power Conditioned Motors”, University Press, 2005.4. Bimal K Bose, “Power Electronics and Variable Frequency Drives - Technology and Application”, IEEE Press, NewYork,
1997. 5. Peter Vas, “Vector Control of AC Machines”, Oxford University Press, 1990.6. Krishnan R, “Electric Motor Drives: Modelling, Analysis and Control”, Prentice Hall of India Pvt. Ltd, New Delhi, 2002.7. Muhammad H Rashid, “Power Electronics Handbook”, Academic press, 2001.
09EC07 NON LINEAR CONTROL3 0 0 3
INTRODUCTION TO LINEARIZATION PROCESS: Common Nonlinear behavior, Common Nonlinearities - Autonomy - Equilibrium points of nonlinear systems, Feedback Linearization, Series Approximation Methods. (9)
168
DESCRIBING FUNCTION: Describing function for different nonlinearities - ideal relay, hysteresis, dead zone, saturation - Stability analysis of systems by describing function - Stable and unstable limit cycle - Dual Input Describing Function - DIDF for typical nonlinearities .
(9)
PHASE PLANE ANALYSIS: Singular points - Construction of phase plane using Isocline, Lienard, Delta and Pell's methods - Poincare index and Bendixon theorems-Stability,determination - Limit cycles -Nonlinear performance analysis of piecewise linear system.
(10)
STABILITY ANALYSIS: Lyapunov Stability, On - Off Control System: Solution of equation - Relay with lead circuit - Popov method - Generation of Liapunov function - Gradient, Lure and Krasoviski method.
(8)
SLIDING MODE CONTROL: Variable structure systems - Basic concepts - Sliding modes in variable structure system conditions for existence of sliding regions – Case Study - Sliding mode approach to speed control of dc motors. (6)
Total 42
REFERENCES:1. John E Gibson, “Non linear Automatic Control”, McGraw Hill Inc., 1963.2. M Gopal, “Digital Control and State Variable Methods, Conventional and Intelligent Control Systems”, McGraw-Hill Inc., New Delhi, Third Edition, 2009.3. Hasen K Khalil, "Nonlinear Systems", Prentice Hall Inc., New York, 1996.4. Jean Jacques Slotine and Weiping Li, “Applied Nonlinear Control”, Prentice Hall Inc., 1991. 5. Katsuhiko Ogata, “Modern Control Engineering”, Prentice Hall Inc., 1997.
09EC08 CONTROL SYSTEMS DESIGN 3 0 0 3
ROOT LOCUS: Review of root locus construction – Design of feedback compensators using root locus. Controller synthesis. Fixed order controllers.
(8)
SYSTEM COMPENSATION: Classical design Examples - Realisation of compensating networks - Lead, Lag, Lag Lead networks - Design of lead compensation - Lag compensation - Lag lead compensation - network compensation using bode plots.
(9)
THREE TERM CONTROLLERS: P, PI, PD, PID Controller Basic control action - Design of Proportional controller – Derivative, Integral controllers - Effects of Derivative, Integral control actions – Tunable PID Controllers – Ziegler – Nichols Methods for Controller Tuning.
(9)
STATE VARIABLE DESIGN: Design by State feedback - output feedback - pole assignment techniques - design of state and output regulators - design of reduced and full order observers.
(8)
ROBUST CONTROL SYSTEMS: Introduction – System Sensitivity – Analysis of Robustness – Systems with uncertain Parameters – Design of Robust Control Systems – Design examples – Robust Internal Model Control Systems – Pseudo – Quantitative Feedback Systems.
(8)
Total 42
REFERENCES:1. Nagrath I J and Gopal M, “Control Systems Engineering”, New Age International Publishers, Fifth Edition, 2008.2. Gopal M, “Control Systems Principles and Design”, Tata McGraw Hill Publishing Company Limited, Eighth Edition, 2008.3. Katsuhiko Ogata, “Modern Control Engineering”, Pearsons Education, Fourth Edition, 2004.4. Richard C Dorf and Robert H Bishop, “Modern Control Systems,” Pearson Education, Eleventh Edition, 2008.5. Dale Seborg, Thomas Edgarand and Duncan Mellichamp, “Process Dynamics and Control”, John - Wiley & Sons Inc., Second Edition, 2006.
09EC09 PROCESS CONTROL3 0 0 3
MATHEMATICAL MODELING OF PROCESSES: Introduction of Process – Need for Process Control –PI Diagrams– Feedback Control Concept- Mathematical model of first order liquid level and thermal processes – Higher order process – Process with dead time, process with inverse response – Interacting and non-interacting systems – Continuous and batch
169
process – Servo and regulator operation. Response of simple closed loop systems. (10)
CONTROLLER CHARACTERISTICS, TUNING AND PROCESS IDENTIFICATION: Basic control action – Characteristics of ON-OFF, proportional, integral and derivative control modes – Composite control modes – P+I, P+D and P+I+D control modes – Electronic controllers to realize various control actions – Evaluation criteria – IAE, ISE, ITAE and ¼ decay ratio – Tuning of controllers – Ziegler-Nichol’s method and Cohen Coon method – Damped oscillation method. Process Identification – Open loop Identification Method – First Order and Second Order Model – Closed loop Identification.
(10)
CONTROL SCHEMES WITH MULTIPLE LOOPS: Cascade control – Feed forward control – Ratio control – Selective control systems – Internal Model Control -Split range control – Adaptive and inferential control – Dead Time Compensation. (8)
ADVANCED PROCESS CONTROL: Basic building blocks of computer control system-multi loop controllers-- Model Reference Predictive Control-Advanced concepts on PID controllers-set point weighting, series and parallel PID controller. (8)
CASE STUDY : Case study of control schemes for – Evaporator – Dryer – Distillation process –binary distillation column. (6)
Total 42REFERENCES:1. Donald R Coughanowr, “Process Systems Analysis and Control”, Tata McGraw Hill Inc., Publishing Company Ltd., 2006.2. Stephanopoulos G, “Chemical Process Control”, Prentice Hall of India, New Delhi, 2001.3. Liptak B G, “Process Control”, Chilton Book Company, 2005.4. Curtis D Johnson, “Process Control Instrumentation Technology”, Eighth Edition, Pearson Education, New Delhi, 2007.
09EC11 ROBUST CONTROL 3 0 0 3
INTRODUCTION: Concepts of model uncertainty, including both parametric and dynamic uncertainty. Fundamental concept of robustness and the relationship between physical systems and mathematical models. Mathematical background including norms for vectors, matrices, signals, and systems. Co prime Factorization and stabilizing controllers, singular value decomposition and its application to perturbation analysis.
(9)
MODELLING OF UNCERTAIN SYSTEMS: Unstructured Uncertainties, Parametric Uncertainty, Linear fractional transformations and canonical forms. Structured Uncerainty. Robust stability and performance problems.
(7)
ROBUST DESIGN SPECIFICATIONS: Small gain theorem and Robust Stabilization, Performance Consideration, Structured Singular Values. H – infinity design: Mixed Sensitivity H-infinity Optimization. H-infinity suboptimal solutions, Discrete time cases.
(9)
H-INFINITY LOOP SHAPING DESIGN: Robust Stabilization against normalised Coprime Factor Perturbations, Loop Shaping Design, Discrete time case. Mixed Optimization Design Method with LSDP. µ- Analysis and Synthesis: Consideration of Robust performance, µ-synthesis- D-K Iteration method, µ-K Iteration method.
(10)
LOWER ORDER CONTROLLERS: Absolute-error Approximation Methods, Reduction via Fractional Factors, Relative-error Approximation Methods, Frequency Weighted Approximation Methods.
(7)
Total 42
REFERENCES:1. Kemin Zhou and John Doyle, “Essentials of Robust Control”, Prentice-Hall Inc., 1998.2. Skogestad and Postlethwaite, “Multivariable Feedback Control: Analysis and Design”, John-Wiley & Sons Inc., 2005.3. Gu D W, Petkov, Konstantinov M M, “Robust Control with MATLAB”, Springer, 2005.4. Zhou K, Doyle J C and Glover K, “Robust and Optimal Control”, Prentice-Hall Inc., 1996.
09EC12 OPTIMAL CONTROL SYSTEM
170
3 0 0 3
OPTIMAL CONTROL PROBLEMS: Statement of optimal control problem - Problem formulation and types of optimal control - Selection of performance measures, General Model of feedback control systems, Transient performance analysis, Tracking performance analysis, Disturbance rejection analysis, Cost functions and norms, Mathematical preliminary to optimal control.
(5) CALCULUS OF VARIATION AND HAMILTON FORMULATION: Fundamental concepts - Extremum functionals involving single and several independent functions – Piecewise smooth extremals - Variation of functionals with fixed and free terminal time constrained extrema Pontryagin's minimum principle - State inequality constraints - The Weierstrass Erdmann corner conditions - Solution of Bolza problem. Partial differential equation for cost function - Hamilton Jacobi equation - Principle of optimality, solution of Hamilton Jacobi equation - Matrix Riccati equation - Optimal control law.
(14)
LINEAR QUADRATIC CONTROL PROBLEMS: Optimal control by Liapunov method - Parameter optimization – Quadratic performance index - Optimal control of systems - Matrix Riccati equation and solution methods of State regulator and discrete systems - Choice of weighting matrices – Linear Quadratic Guassian control – Kalman filter – H 2 and H Control and Optimal estimation.
(7)
DYNAMIC PROGRAMMING: Principle of optimality - Recurrence relation of dynamic programming for optimal control problem - Combinational procedure for solving optimal control problem.
(6)
DISCRETE TIME SYSTEMS: Solution of general discrete optimization problem - Discrete time linear quadratic regulator - Suboptimal feedback - Regulator problem with functions of final state fixed. Time optimal and fuel optimal control problems - Minimum time control problem, Uniqueness of control - Bang bang control – Case study-Aero space applications-Fuel optimal systems.
(10)
Total 42
REFERENCES:1. Kirk D E, “Optimal Control Theory: An Introduction”, Prentice Hall, New Jersey, 2008.2. Brian D O Anderson and John B Moore, “Optimal Control - Linear Quadratic Methods”, Prentice Hall of India, 1991.3. Jeffrey B Burl, “Linear Optimal Control”, Addison-Wesley, California, 1999.4. Frank L Lewis, “Optimal Control”, John Wiley & Sons, New York, 1986.5. Gopal M, “Modern Control System Theory”, Wiley Eastern, New Delhi, second Edition, 1993.6. Michael Athens. “Optimal Control”, Tata McGraw Hill Publishing Company Ltd., 1996.
09EC13 ADAPTIVE CONTROL SYSTEM3 0 0 3
INTRODUCTION TO ADAPTIVE CONTRO: Development of adaptive control problem-The role of Index performance (IP) in adaptive systems- Development of IP measurement process model.
(4)
SYSTEM RESPONSE IDENTIFICATION: Identification by Cross Correlation - Synthesis techniques for flat spectrum Pseudo random signals - Quasi linearization -Impulse response expansion-Identification using matched filter, Adaptive control using steepest Descent.
(7)
PERTURBATION SYSTEMS: Single and Multi-dimensional adaptive systems – Stability Analysis of Sinusoidal perturbation adaptive controllers – Formulation of signal synthesis system.
(6)
SELF TUNING REGULATORS (STR) AND MODEL REFERENCE ADAPTIVE SYSTEMS: Introduction - Pole placement design-Indirect Self-tuning regulators - Continuous time Self-Tuners - Direct self tuning regulators - Linear quadratic self - Tuning regulators - Adaptive predictive control. The MIT rule – Determination of Adaptation Gain – Design of MRAS using Liapunov theory – BIBO Stability – Applications to Adaptive control- Model Free Adaptive Control.
(14)
GAIN SCHEDULING: Principle-Design of Gain Scheduling Controllers - Nonlinear Transformations of second Order Systems Applications of Gain Scheduling. Case study - ABB Adaptive Controllers, Satt Control ECA40, The First Control Adaptive Controller.
(11)
Total 42
REFERENCES:
171
1. Karl J Astrom and Bjorn Wittenmark, “Adaptive Control”, Pearson education Inc., New Delhi, second Edition, 2008.2. Shankar Sastry and Marc Bodson, “Adaptive Control – Stability, Convergence and Robustness”, Prentice Hall,
Englewood Cliffs, New Jersey, 1989.3. Ljung L, “System Identification: Theory for the user”, Prentice Hall, Englewood Cliffs,1999.4. Chalam V V, “Adaptive Control Systems – Techniques and Applications “, Marcel Dekkar Inc., NewJersey, 1987.5. Kumpathi S Narendra, Romeo Ortega and Peder Dorator, “Advances in Adaptive Control”, IEEE Press, NewJersey,
1991.6. Petros A Ioannov and Jing Sun, “Robust Adaptive Control”, Prentice Hall Inc., 1996.
09EC14 LOGIC AND DISTRIBUTED CONTROL SYSTEM3 0 0 3
REVIEW OF COMPUTERS IN PROCESS CONTROL: Direct Digital Control (DDC). Supervisory Control and Data Acquisition Systems (SCADA), sampling considerations. Functional block diagram of computer control systems. alarms, interrupts. Characteristics of digital data, controller software, linearization. Digital controller modes: Error, proportional, derivative and composite controller modes.
(8)
PROGRAMMABLE LOGIC CONTROLLER (PLC) BASICS: Definition, overview of PLC systems, input/output modules, power supplies, isolators. General PLC programming procedures, programming on-off inputs/ outputs. Auxiliary commands and functions: PLC Basic Functions: Register basics, timer functions, counter functions.
(9)
PLC INTERMEDIATE FUNCTIONS: Arithmetic functions, number comparison functions, Skip and MCR functions, data move systems. PLC Advanced intermediate functions: Utilizing digital bits, sequencer functions, matrix functions. PLC Advanced functions: Alternate programming languages, analog PLC operation, networking of PLC, PLC-PID functions, PLC installation, troubleshooting and maintenance, design of interlocks and alarms using PLC. Creating ladder diagrams from process control descriptions. Interface and backplane bus standards for instrumentation systems.
(9)
DISTRIBUTED CONTROL SYSTEMS (DCS): Definition, Evolution of DCS, Generalized architecture of DCS, Local Control Unit (LCU), LCU languages. (8)
CONFIGURATION OF DCS: LCU - Process interfacing issues, communication facilities, high level and low level operator interfaces - displays, redundancy concept.
(8)
Total 42
REFERENCES:1. Curtis D Johnson, “Process Control Instrumentation Technology”, Prentice Hall of India, New Delhi, Fourth edition,
1999.2. John W Webb and Ronald A Reis , “Programmable Logic Controllers – Principles and Applications”, Prentice Hall Inc.,
New Jersey, Third edition , 2003.3. Frderick D Hackworth and John R Hackworth, “Programmable Logic Controllers; Programming Methods and
Applications”, Pearson Education, 2005.4. Frank D Petruzella, “Programmable Logic Controllers”, McGraw- Hill Inc., 1998.5. Lukcas M P, “Distributed Control Systems”, Van Nostrand Reinhold Co., New York, 1986. 6. Deshpande P B and Ash R H, “Elements of Process Control Applications”, ISA Press, New York, 1995.
09EC15 ROBOTICS AND AUTOMATION3 0 0 3
FUNDAMENTAL CONCEPTS OF ROBOTICS: History, Present status and future trends in Robotics and automation - Laws of Robotics - Robot definitions - Robotics systems and robot anatomy - Specification of Robots - resolution, repeatability and accuracy of a manipulator - Robotic applications.
(8)
ROBOT DRIVES AND POWER TRANSMISSION SYSTEMS: Robot drive mechanisms, hydraulic – electric – servomotor- stepper motor - pneumatic drives, Mechanical transmission method - Gear transmission, Belt drives, cables, Roller chains, Link - Rod systems - Rotary-to-Rotary motion conversion, Rotary-to-Linear motion conversion, Rack and Pinion drives, Lead screws, Ball Bearing screws, End effectors – Types.
(9)
VISION SYSTEMS FOR ROBOTICS: Robot vision systems, Image capture- cameras – vidicon and solid state, Image representation - Gray scale and colour images, image sampling and quantization - Image processing and analysis - Image data reduction - Segmentation - Feature extraction - Object Recognition- Image capturing and communication - JPEG, MPEGs and H.26x standards, packet video, error concealment.- Image texture analysis – Machine vision, vision guided motion. (8)
TRANSFORMATIONS AND KINEMATICS: Homogeneous coordinates – Coordinate reference frames - Homogeneous transformations for the manipulator - The forward and inverse problem of manipulator kinematics - Motion generation -
172
Manipulator dynamics - Jacobean in terms of D-H matrices - Controller architecture. (8)
FACTORY AUTOMATION: Flexible Manufacturing Systems concept - Automatic feeding lines, ASRS, transfer lines, automatic inspection - Computer Integrated Manufacture - CNC, intelligent automation. Industrial networking, bus standards, HMI Systems, DCS and SCADA, Wireless controls.
(9).
Total 42
REFERENCES:1. Mittal R K and Nagarath I J, “Robotics and Control”, Tata McGraw Hill, 2005.2. Saeed B Niku, “Introduction to Robotics Analysis, Systems, Applications”, Prentice Hall of India P Ltd, New Delhi,2003.3. Klafter R D, Chmielewski T A and Michel Negin, “Robotics Engineering, An Integrated approach”, Prentice Hall of India,
2003.4. Fu K S, Gomalez R C and Lee C S G, “Robotics: Control, Sensing, Vision and Intelligence”, McGraw Hill Book Company, 1987.
09EC16 STATE ESTIMATION AND PARAMETER IDENTIFICATION3 0 0 3
SYSTEM MODELS WITH STOCHASTIC PROCESS: Probability functions - Expected value and characteristics function - Independence and correlation - Gaussian distribution - Gauss Markov sequence model - Gauss Markov process model - Bayesian estimate concepts.
(5)
OPTIMAL FILTERING AND PREDICTION: Estimation of continuous linear systems - Wiener Hopf Integral equation - Continuous Kalman filter - Estimation of discrete system - Kalman filter , Information filter, Extended Kalman Filter, Extended Information filter. Unscented Kalman Filter. Particle filter, Decentralized Estimation for multisensor systems
(10)
OPTIMAL SMOOTHING: Types of smoothing - Fixed Interval - Fixed Point - Fixed lag, single and double stage optimal smoothing - Discrete and continuous system formulations - Bayes, Minimax and MAP estimation concepts.
(8)
PARAMETER IDENTIFICATION: Regression techniques - Regression curves and planes - Estimation from a finite number of observations - Identification of linear dynamic process - Transfer function models - Linear regression sequential regression methods.
(9)
The scalar case – Multi parameter case - Sequential nonlinear regression - A stochastic approach to identification - Sequential learning identification. Quasilinearization Approach : Quasi linearization identification of continuous systems and of discrete systems - Input output methods-Case studies- Diagnosis of Faults.
(10)
Total 42
REFERENCES:1. Sykhoff P, “System Identification Parameter and State Estimation”, John Wiley and Sons, London, 1974.2. Daniel Graupe, “Identification of Systems”, Van Nostrand Reinhold Company, New York, 1972.3. Sage A P and Melsa J L, “System Identification”, Academic Press, 1971.4. Eykhoff P, “Identification and System Parameter Estimation Part 1 & 2”, Proceedings of third IFAC Symposium, North
Hollard Pub. Co., Amsterlam, The Netherlands, 1974.5. Desai R C and Lalwani C S, “Identification Techniques”, Tata McGraw Hill, New Delhi, 1974.6. Kailath T, Hassibi B and Sayed A H, “Linear Estimation”, Prentice Hall of India, New Delhi, 2000.7. Ljung L, “System Identification: Theory for the user”, Prentice Hall, Englewood Cliffs, 1999.8. Arthur Gelb, “Applied Optimal Estimation”, The MIT Press, 1974.9. Arthur G O Mutambara, “Decentralized Estimation and Control for Multisensory Systems”, CRC, 1998.
09EC17 MICRO ELECTRO MECHANICAL SYSTEMS
3 0 0 3
MEMS AND MICROSYSTEMS AND SCALING LAWS IN MINIATURIZATION: MEMS and microsystem products. Evaluation of microfabrication. Microsystems and microelectronics. Applications of microsystems. Working principles of microsystems-microsensors, microactuators, MEMS and microactuators, microaccelerometers. Scaling Laws: Scaling in rigid body dynamics.
173
The Trimmer force scaling vector-scaling in electrostatic forces, electromagnetic forces, scaling in electricity and fluidic dynamics, scaling in heat conducting and heat convection. (10)
MATERIALS FOR MEMS AND MICROSYSTEMS: Substrates and wafers-silicon as a substrate material, ideal substrates for MEMS. Single crystal Silicon and wafers crystal structure. Mechanical properties of Si. Silicon compounds-SiO2, SiC, Si3N4 and polycrystalline Silicon. Silicon piezoresistors. Gallium arsenside. Quartz-piezoelectric crystals. Polymers for MEMS. Conductive polymers. (8)
ENGINEERING MECHANICS FOR MICROSYSTEMS DESIGN: Static bending of thin plates-circular plates with edge fixed, square plates with all edges fixed. Mechanical vibration. Resonant vibration. Microaccelerometers-design theory and damping coefficients. Thermomechanics. Thermal stresses. Fracture mechanics.Fluid mechanics: Viscosity of fluids. Basic equation in continuum fluid dynamics. Laminar fluid flow in circular conduits. Computational fluid dynamics. Incompressible fluid flow in microconducts-surface tension, capillary effect and micropumping. Fluid flow in submicrometer and nanoscale-rarefied gas, Kundsen and Mach number and modelling of microgas flow. Heat conduction in multilayered thin films. (10)
MICROSYSTEM FABRICATION PROCESSES: Photolithography. Photoresist and applications. Light sources. Ion implanation. Diffusion process. Oxidation-thermal oxidation. Silicon diode. Thermal oxidation rates. Oxide thickness by colour. Chemical vapour deposition-principle, reactants in CVD. Enhanced CVD physical vapour deposition. Sputtering. Deposition by epitaxy. Etching-chemcial and plasma etching. (7)
MICROMANUFACTURING AND MICROSYSTEM PACKAGING: Bulk micromachining. Isotropic and anisotropic etching-wet etchants, etch stops, dry etching comparison of wet and dry etching. Surface micromachining-process in general, problems associated in surface micromachining. The LIGA process-description, materials for substrates and photoresists, electroplating, the SLIGA process. Microsystem packaging-general considerations. The three levels of microsystem packaging-die level, device level and system level. Essential packaging technologies-die preparation-surface bonding, wire bonding and sealing. Three dimensional packaging. Assembly of microsytems-selection of packaging materials. (7)
Total 42
REFERENCES:1. Tai Ran Hsu, “MEMS and Microsystems Design and Manufacture“, Tata McGraw Hill Publishing Co. Ltd., New Delhi, 2002.2. Mark Madou “Fundamentals of Micro fabrication”, CRC Press, New York, 1997.3. Julian W Gardner, “Micro sensors: Principles and Applications”, John Wiley and Sons, New York, 2001.4. Chang C Y and Sze S M, “VLSI Technology”, Mc Graw Hill, New York, 2000.5. Kovacs G T A, “Micro machined Transducers Sourcebook”, McGraw Hill, New York, 1998.6. Julian W Gardner, Vijay K Varadan and Awadelkarim O O, “Microsensors, MEMS and Smart Devices”, John Wiley & Sons Inc., 2001.
09EC18 INDUSTRIAL DATA NETWORKS3 0 0 3
INTRODUCTION: Modern Instrumentation and Control Systems- Introduction to Networks-Advantages and Disadvantages. OSI Model-Foundations of OSI Model. Protocol – Standards. Grounding, Shielding & Noise. Basics of Digital Modulation techniques. EIA-232-Overview. EIA-485- Overview. Current loop & EIA Converters.
(9)
INDUSTRIAL ETHERNET: Introduction-IEEE Standards-Ethernet MAC layer-IEEE 802.2 and Ethernet SNAP- OSI and IEEE 802.3 standard. Ethernet transceivers, Ethernet types, switches & switching hubs, 10 Mbps Ethernet, 100 Mbps Ethernet, Gigabit Ethernet. TCP / IP Overview- Internet Layer Protocols- Host-to-Host layer.
(10)
MODBUS: Overview-Protocol Structure-Example Function codes. Modbus Plus protocol- Overview. Data Highway Plus- Overview. AS – interface Overview- Layers- Operating Characteristics.
(8)
DEVICENET: Overview – Layers. Profibus-Overview-Protocol Stack. HART Protocol – Overview- Layers. Foundation Field Bus- Layers-Error Detection and Diagnostics. CAN bus – Overview- Layers. Local Interconnect Networks, Redundancy. (8)
RADIO AND WIRELESS COMMUNICATION: Introduction-Components of a radio link. Radio Spectrum and Frequency allocation. Radio Modems. Intermodulation and prevention. Implementing a radio link.
(7)
Total 42REFERENCES:1. Steve Mackay, Edwin Wright and Deon Reynders, “Practical Industrial data Networks: Design, Installation and Trouble
Shooting”, Elsevier International Projects Ltd., 2004.2. Behrouz A Forouzan, “Data Communications and Networking”, Tata McGraw-Hill, 2000.3. William Buchanan, “Computer Buses- Design and Application”, CRC Press, 2000.4. Theodore S Rappaport, “Wireless Communications: Principles and Practice”, Prentice Hall PTR, Second Edition, 2002.
09EC19 EMBEDDED SYSTEMS3 0 0 3
174
INTRODUCTION TO EMBEDDED SYSTEMS: Embedded Systems-Applications of Embedded Systems-Processors in the System-Other Hardware Units-Software Embedded into a System-Exemplar Embedded Systems-Embedded System-on-Chip (SOC) and in VLSI circuit.
(8)
DEVICES AND BUSES FOR DEVICE NETWORK: I/O Devices-Timer and Counting Devices-Serial Communication using I2C, CAN and USB. Parallel Communication using PCI, PCIX and Advanced Parallel High Speed Buses.
(8)
DEVICE DRIVERS AND INTERRUPTS SERVICING MECHANISM: Device Drivers-Parallel Port Device Drivers in a System, Serial Port Device Drivers in a System, Device Drivers for Internal Programmable Timing Devices – Interrupt Servicing Mechanism-Context and the Periods for Context Switching, Deadline and Interrupt Latency.
(8)EMBEDDED SOFTWARE DEVELOPMENT USING IDE: Introduction to Integrated Development Environment (IDE)- Programming Concepts and Embedded Programming in Assembly and C- Creating a New Project – Adding Files to a Project-Building a Project-Debugging and Simulating the application-Getting Embedded Software into the Target System.
(8)
REAL TIME OPERATING SYSTEMS (RTOS): Tasks and Task States, Tasks and Data, Semaphores and Shared Data, Message Queues, Mailboxes and Pipes, Timer functions, Events, Memory Management, Interrupt Routines in RTOS Environment - Case study - Embedded control of Process parameters.
(10) Total 42
REFERENCES:
1. Rajkamal, “Embedded Systems: Architecture, Programming and Design”, Tata McGraw-Hill, 2006. 2. David E Simon, “An Embedded Software Primer” Pearson Education Asia, 2006.3. Arnold Berger, “Embedded System Design: An Introduction to Processes, Tools, and Techniques”, CMP Books, 2001.4. Wayne Wolf, “Computers as Components” Morgan Kaufmann Publishers, 2005.5. Douglas V Hall, “Microprocessors and Interfacing: Programming and Hardware”, Tata McGraw-Hill, Second Edition, 2001.
09EC20 INTELLIGENT CONTROLLERS3 0 0 3
INTRODUCTION TO NEURAL NETWORKS: Artificial Neural Networks: Basic properties of Neurons, Neuron Models, Feed forward networks – Perceptrons, widrow-Hoff, LMS algorithm; Multilayer networks – Exact and approximate representation, Back propagation algorithm, variants of Back propagation, Unsupervised and Reinforcement learning; Symmetric Hopfield networks and Associative memory; Competitive learning and self organizing networks, Hybrid Learning; Computational complexity of ANNs.
(9)
NEURAL NETWORKS 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 an chemical process, Auto – turning feedback control, industrial distillation tower.
(9)
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.
(8)
FUZZY LOGIC BASED CONTROL: Fuzzy Controllers: Preliminaries – Fuzzy sets in commercial products – 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. A hybrid neural network based Fuzzy controller with self learning teacher. Fuzzified CMAC and RBF network based self-learning controllers.
(8)
GENETIC ALGORITHM: Basic Concepts - Working Principle- Encoding - Fitness Function- Reproduction - Inheritance operators - Cross over, Inversion and Deletion, mutation operator, Bitwise operator - Generation Cycle- Convergence of Genetic Algorithm- applications.
(8)
Total 42
REFERENCES:1. Rajasekaran S and Vijayalakshmi Pai G A, “Neural Networks, Fuzzy Logic and Genetic Algorithms-Synthesis and
Applications”, Prentice Hall of India, 2007.2. Zurada J M, “Introduction to Artificial Neural systems”, Jaico Publishing House, Bombay, 2001.3. Timothy Ross, “Fuzzy Logic with Engineering Applications”, Mc Graw Hill, Singapore, 1998.5. Zimmermann H J, “Fuzzy set Theory and its Applications”, Allied Publishers Ltd, New Delhi, 1999.6. Klir G J, and Folger T, “Fuzzy Sets, Uncertainty and Information”, Prentice Hall of India, New Delhi, 2002.
175
7. Hans Hellendoorn and Dimiter Driankov, “Introduction to Fuzzy Control”, Narosa Publisher ,2001.8. Mohammad H Hassoun, “Fundamentals of Neural Networks”, Prentice Hall of India, New Delhi, 1998. 9. Metanie Mitchell, “An Introduction to Genetic Algorithms”, Prentice Hall of India, New Delhi, 200410. Kosco B, “Neural Networks and Fuzzy Systems: A Dynamic Approach to Machine Intelligence”, Prentice Hall of India,
New Delhi, 1992.
09EC41 INDUSTRIAL VISIT AND TECHNICAL SEMINAR1 0 2 2
The student will make atleast two technical presentations on current topics related to the specialization. The same will be assessed by a committee appointed by the department. The students are expected to submit a report at the end of the semester covering the various aspects of his/her presentation together with the observation in industry visits. A quiz covering the above will be held at the end of the semester.
09EC51 PROCESS CONTROL LABORATORY0 0 3 2
1. Obtaining Mathematical Model of a process plant.2. Tuning of a PID controller.3. Cascade control of a process.4. Feed forward control of a process.5. Control of a process using auto tuning controller.6. Characteristics of pneumatic control valves.7. Design of Temperature transmitter.8. AC Servomotor Control.9. DC Servomotor Control.10. Study of Fieldbus protocol.
09EC52 INDUSTRIAL AUTOMATION LABORATORY0 0 3 2
1. Identification of a system model.2. Implementation of state estimator in real time.3. Implementation of wireless closed loop system.4. Implementation of Digital Control Algorithm using C/C++.5. Implementation of LQG controller.6. Control of a system using variable structure controller.7. Control system design using MATLAB/Simulink.8. Design and Implementation of instrument network.9. Control of a sequential process using PLC. 10. Study of SCADA and DCS.
09EC55 OBJECT COMPUTING AND DATA STRUCTURES LABORATORY
2 0 3 4
PRINCIPLES OF OOP: Programming paradigms, basic concepts and benefits of OOP, applications of OOP. (2)
INTRODUCTION TO C++: History of C++, structure of C++, basic data types, derived data types, symbolic constants, dynamic initialization, type modifiers, type casting, operator and control statements, input and output statements. (3)
CLASSES AND OBJECTS: Class specification, member function specification , scope resolution operator, access qualifiers, instance creation, member functions, function prototyping, function components, passing parameters, call by reference, return by reference, inline function, default arguments, overloaded function. Array of objects, pointers to objects, this pointer, dynamic allocation operators, dynamic objects. Constructors, parameterized constructors, overloaded constructors, constructors with default arguments, copy constructors, static members and static objects as arguments, returning objects, friend function and friend class.
(7) OPERATOR OVERLOADING: Operator function, overloading unary and binary operator, overloading the operator using friend function.
(2)
176
INHERITANCE: Defining derived class, single inheritance, protected data with private inheritance, multiple inheritance, multi level inheritance, hierarchical inheritance, hybrid inheritance, multipath inheritance, constructors in derived and base classes, abstract classes.
(5)
INTRODUCTION TO DATA STRUCTURES: Abstract data types, primitive data structures, analysis of algorithms, notation.
(5)
ARRAYS: Operations, implementation of one, two and multi dimensioned arrays, different types of array applications. (5)
STRINGS: Implementation, Operations, applications. (3)
STACKS: Primitive operations, sequential implementation, applications. Recursion definition, process and implementation using stacks, evaluation of expressions.
(3)
QUEUES: Primitive operations, sequential implementation, applications. Priority queues, dequeues. (3)
SORTING: Insertion sort, selection sort, bubble sort, heap sort, radix sort algorithms and analysis. (4)
Total : 42
REFERENCES:1. Bjarne Stroustrup, “The C++ Programming Language”, Addison Wesley, 2004. 2. Stanley B Lippman and Josee Lajoie, “The C++ Primer”, Addison Wesley, 2005.3. Harvey M Deitel,and Paul J. Deitel, “C++ How to Program”, Prentice Hall, 2007.4. Aaron M Tanenbaum, Moshe J Augenstein and Yedidyah Langsam, “Data structures using C and C++”, Prentice Hall of India, 2005.5. Sahni Sartaj, “Data Structures, Algorithms and Applications in C++”, Universities Press, 2005.6. Nell Dale, “C++ Plus Data Structures”, Jones and Bartlett, 2006.7. Mark Allen Weiss, “Data Structures and Algorithm Analysis in C++”, Addison-Wesley, 2006.8. Robert L Kruse and Clovis L Tondo, “ Data Structures and Program design in C”, Pearson Education, 2005.
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