Syllabus for credit based curriculum 2010 – 2011 onwards

Multisensor data fusion: Introduction, sensors and sensor data, Use of multiple sensors, Fusion applications. The inference hierarchy: output data. Data fusion model. Architectural concepts and issues. Benefits of data fusion, Mathematical tools used: Algorithms, co-ordinate transformations, rigid body motion. Dependability and Markov chains, Meta – heuristics.

Taxonomy of algorithms for multisensor data fusion. Data association. Identity declaration.

Estimation: Kalman filtering, practical aspects of Kalman filtering, extended Kalmal filters. Decision level identify fusion. Knowledge based approaches.

Data information filter, extended information filter. Decentralized and scalable decentralized estimation. Sensor fusion and approximate agreement. Optimal sensor fusion using range trees recursively. Distributed dynamic sensor fusion.

High performance data structures: Tessellated, trees, graphs and function. Representing ranges and uncertainty in data structures. Designing optimal sensor systems with in dependability bounds. Implementing data fusion system.

TEXT BOOKS:

1. 
   David L. Hall, Mathematical techniques in Multisensor data fusion, Artech House, Boston, 1992.
   
2. 
   R.R. Brooks and S.S. Iyengar, Multisensor Fusion: Fundamentals and Applications with Software, Prentice Hall Inc., New Jersey, 1998.
   

REFERENCES:

1. 
   Arthur Gelb, Applied Optimal Estimation, The M.I.T. Press, 1982.
   
2. 
   James V. Candy, Signal Processing: The Model Based Approach, McGraw –Hill Book Company, 1987.
   

CL 669 OPTIMAL CONTROL THEORY

Problem formulation – Mathematical model – Physical constraints - Performance measure Optimal control problem. Form of optimal control. Performance measures for optimal control problem. Selection a performance measure.

Dynamic Programming – Optimal control law – Principle of optimality. An optimal control system. A recurrence relation of dynamic programming – computational procedure. Characteristics of dynamic programming solution. Hamilton – Jacobi – Bellman equation. Continuous linear regulator problems.

Calculus of variations – Fundamental concepts. Functionals. Piecewise – smooth extremals Constrained extrema.

Variational approach to optimal control problems – Necessary conditions for optimal control – Linear regulator problems. Linear tracking problems. Pontryagin’s minimum principle and state inequality constraints.

Minimum time problems – Minimum control – effort problems. Singular intervals in optimal control problems. Numerical determination of optimal trajectories – Two point boundary – valve problems. Methods of steepest decent, variation of extremals. Quasilinearization. Gradient projection algorithm.

TEXTBOOK:

1. 
   Donald E. Kirk, Optimal Control Theory: An Introduction, Prentice-Hall networks series, 1970.
   

REFERENCES:

1. 
   Anderson .B. D. O, Moore .J. B, Optimal control linear Quadratic methods, Prentice Hall of India, New Delhi, 1991.
   
2. 
   Sage A. P, White .C. C, Optimum Systems Control, Second Edition, Prentice Hall, 1977.
   

CL 670 STOCASTIC PROCESSES AND ESTIMATION THEORY

Introduction to Probability, Random variables. Discrete probability distribution functions. Cumulative, Joint and conditional probability density and distribution functions. Statistical Independence, Vector random variables. Expectation of a random variable, characteristic function, Central limit theorem.

Random Processes: Ensemble, examples of random processes, Markov chains, random walk and difference equations, Hidden Markov processes. Correlation. Stationary random processes. Properties of autocorrelation function. Random sequences. Cross correlation functions by ensemble averaging properties. Power spectral density function. Cross spectral density functions. Ergodic random processes.

Estimation: Introduction, development of parameter estimators, estimation of stochastic processes, applications. Least – square estimation. Linear least squares problem, generalized least square problem. Sequential least squares, non-linear least squares theory.

Characteristics of estimators: Sufficient statistics, Good estimators. Analysis of estimation errors. Mean square and minimum variance estimators.

Maximum a posteriori and maximum likelihood estimators. Numerical solution of least – squares and maximum likelihood estimation problems. Sequential estimators and some asymptotic properties.

TEXT BOOKS:

1. 
   Childers, Probability and random processes, The McGraw-Hill companies Inc., 1997.
   
2. 
   Harold W. Sorenson, Parameter Estimation, Principles and Problems, Marcel Dekker Inc., 1980.
   

CL 671 BIOPROCESS ENGINEERING
General requirements of fermentation processes- An overview of aerobic and anaerobic fermentation processes and their application in industry - Medium requirements for fermentation processes - examples of simple and complex media - Design and usage of commercial media for industrial fermentation. Sterilization: Thermal death kinetics of micro-organisms - Batch and Continuous Heat-Sterilization of liquid Media- Filter Sterilization of Liquid Media and Air.
Enzymes: Classification and properties-Applied enzyme catalysis - Kinetics of enzyme catalytic reactions-Metabolic pathways - Protein synthesis in cells.
Stoichiometry of microbial growth, Substrate utilization and product formation-Batch and Continuous culture, Fed batch culture
Operating considerations for bioreactors for suspension and immobilized cultures, Selection, scale-up, operation of bioreactors-Mass Transfer in heterogeneous biochemical reaction systems; Oxygen transfer in submerged fermentation processes; oxygen uptake rates and determination of oxygen transfer rates and coefficients; role of aeration and agitation in oxygen transfer. Heat transfer processes in Biological systems. Recovery and purification of products.
measurement of physical and chemical parameters in bioreactors- Monitoring and control of dissolved oxygen, pH, impeller speed and temperature in a stirred tank fermenter.

TEXT BOOKS:

1. M.L. Shuler and F. Kargi, "Bio-process Engineering", 2 Ed., Prentice Hall of India., New Delhi. 2002.

2. J.E. Bailey and D.F. Ollis," Biochemical Engineering Fundamentals", 2^nd Edn., McGraw Hill Publishing Co. New York, 1985.
REFERENCES:

1. P.Stanbury, A. Whitakar and S.J.Hall, " Principles of Fermentation Technology" 2^nd Edn., Elsevier-Pergamon Press, 1995.
CL 672 DIGITAL CONTROL SYSTEM DESIGN

Discrete time signals, Discrete time systems, Sampling and reconstruction, digitizing analog controllers.

Discrete time state equations, discrete time system response, the characteristic value problem, Uncoupling state equations, Observability and controllability.
Observability and state observation, Estimation and identification, Controllability and state control, State feedback, Output feedback.
Full order state observer, Observer design, Lower-order observers, Eigenvalue placement with observer feedback.
Ideal tracking system design, Response model tracking system design, Reference model tracking system design.
REFERENCES:

1. 
   Gene H. Hostetter, Digital Control System, Second Edition Holt,Rinehart and Winston, Inc.U.S, 1997.
   
2. 
   Ogata K, Discrete Time Control Systems, Pearson Education, 2001.
   
3. 
   Gopal M, Digital Control and State variable Methods, Second Edition, Tata McGrawHill, New Delhi, 2003.
   

CL 673 DISCRETE OUTPUT FEEDBACK CONTROL

Lifting discrete-Time signals, Lifting Discrete time systems, fast discretization of SD systems, Design Examples, Simulation of SD systems.

Lifting continuous time signals, lifting open loop systems, lifting SD feedback systems.
Periodic output feedback control law, controller design and applications, Fast output feedback control law, controller design and applications, Simultaneous control using periodic and fast output control.
Sliding motion, Properties in the sliding mode.
Methods of hyper plane design, VSC design based on state and output feedback. Applications: Manipulator control, Flexible structure control.
REFERENCES:

1. 
   Tongwen Chen and Bruce Francis, “Optimal Sampled – Data Control Systems”, Springer-verlag London Limited, 1995.
   
2. 
   Gene H. Hostetter, “Digital control system design”, Second Edition Holt,Rinehart and Winston, Inc.U.S, 1997.
   
3. 
   Vadim I. Utkin, “Sliding modes in control and optimization”, Springer-verlag, US 1992.
   
4. 
   A.S.I. Zinober,” Deterministic control of uncertain systems”, Peter Peregrinus Ltd. London, 1990.
   

CL 674 CHEMICAL PROCESS FLOWSHEETING

Flowsheeting
Introduction, Symbols, Flowsheet presentation with examples, Manual flowsheet calculation,Constrains and their applications in flowsheet calculations, Types of flow sheets, Synthesis of steady state flow sheet, Flowsheeting software.
Sequential modular approach to flowsheeting
Solution, partitioning and tearing a flowsheet, convergence of tear streams with suitable

example.
Flowsheeting by equation solving methods

Selection, decision and tearing of variables in a flowsheet with simple and complex examples
Flowsheet applications
P & I D development, typical stages of P & I D, Applications of P & I D in design stage - Construction stage - Commissioning stage - Operating stage - Revamping stage - Applications of P & I D in HAZOPS and Risk analysis.
TEXT BOOKS:

1. 
   Ernest E. Ludwig, “Applied Process Design for Chemical and Petrochemical Plants”, Vol.-I Gulf Publishing Company, Houston, 1989.
   
2. 
   Max. S. Peters and K.D.Timmerhaus, “Plant Design and Economics for Chemical Engineers”, McGraw Hill, Inc., New York, 1991.
   

REFERENCES:

1. 
   Anil Kumar,”Chemical Process Synthesis and Engineering Design”, Tata McGraw Hill publishing Company Limited, New Delhi - 1981.
   
2. 
   A.N. Westerberg, et al., “Process Flowsheeting”, Cambridge University Press, 1979.
   

CL 675 REAL TIME AND EMBEDDED SYSTEM
System Design: Definitions, Classifications and brief overview of micro-controllers, microprocessors and DSPs. Embedded processor architectural definitions. Typical application scenarios of embedded systems.
Interface Issues Related to Embedded Systems: A/D, D/A converters, timers, actuators, power, FPGA, ASIC, diagnostic port.
Techniques for Embedded Systems: State Machine and state tables in embedded design, Simulation and Emulation of embedded systems. High-level language descriptions of S/W for embedded system, Java embedded system design.
Real time Models, Language and Operating Systems: Event based, process based and graph based models, Petrinet models – Real time languages – The real time kernel, OS tasks, task state4s, task scheduling, interrupt processing, clocking communication and synchronization, control blocks, memory requirements and control, kernel services.
Case Studies: Discussion of specific examples of complete embedded systems using mc68 HC11, mc8051, ADSP2181, PIC series of microcontroller.
TEXT BOOK AND REFERENCES:

1. 
   Ball S.R, Embedded microprocessor systems – Real World Design, Prentice Hall, 1996.
   
2. 
   Herma K, Real Time Systems – Design for Distributed Embedded Applications, Kluwer Academic, 1997.
   
3. 
   Gassle J, Art of Programming Embedded Systems, Academic Press, 1992.
   
4. 
   Gajski D.D, Vahid F, Narayan S, Specification and Design of Embedded Systems, PRT Prentice Hall, 1994.
   
5. 
   Intel manual on 16-bit embedded controllers, Santa Clara, 1991.
   
6. 
   Slater M, Microprocessor based design, a Comprehensive guide to effective hardware design, Prentice Hall, New Jersey, 1989.
   
7. 
   Peatman, J.B, Design with Micro controllers, McGraw Hill International Ltd., Singapore, 1989.
   
8. 
   C.M. Krishna, Kang G. Shin, Real Time Systems, McGraw Hill, 1997.
   

9. Raymond J.A. Buhr, Donald L. Bailey, An Introduction to Real Time Systems, Prentice Hall International, 1999.

CL 676 VIRTUAL INSTRUMENTATION

Virtual Instrumentation: Historical perspective, advantages, block diagram and architecture of a virtual instrument, data-flow techniques, graphical programming in data flow, comparison with conventional programming. Development of Virtual Instrument using GUI, Real-time systems, Embedded Controller, OPC, HMI / SCADA software, Active X programming.

VI programming techniques: 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, Instrument Drivers, Publishing measurement data in the web.

Data acquisition basics: Introduction to data acquisition on PC, Sampling fundamentals, Input/Output techniques and buses. ADC, DAC, Digital I/O, counters and timers, DMA, Software and hardware installation, Calibration, Resolution, Data acquisition interface requirements.

VI Chassis requirements. Common Instrument Interfaces: Current loop, RS 232C/ RS485, GPIB. Bus Interfaces: USB, PCMCIA, VXI, SCSI, PCI, PXI, Firewire. PXI system controllers, Ethernet control of PXI. Networking basics for office & Industrial applications, VISA and IVI.

VI toolsets, distributed I/O modules. Application of Virtual Instrumentation: Instrument Control, Development of Process database management system, Simulation of systems using VI, Development of Control system, Industrial Communication, Image acquisition and processing, Motion Control.
TEXTBOOKS:

1. 
   Gary Johnson, LabVIEW Graphical Programming, Second edition, McGraw Hill, Newyork, 1997.
   
2. 
   Lisa K. wells & Jeffrey Travis, LabVIEW for everyone, Prentice Hall, New Jersey, 1997.
   

REFERENCES:

1. Kevin James, PC Interfacing and Data Acquisition: Techniques for Measurement, Instrumentation and Control, Newnes, 2000.

WEB RESOURCES:

www.ni.com

www.ltrpub.com