General concepts and terminology of measurement systems, static and dynamic characteristics, errors, standards and calibration.
Introduction, principle, construction and design of various active and passive transducers. Introduction to semiconductor sensors and its applications.
Design of signal conditioning circuits for various Resistive, Capacitive and Inductive transducers and piezoelectric transducer.
Introduction to transmitters, two wire and four wire transmitters, Smart and intelligent Transmitters. Design of transmitters.
Introduction to EMC, interference coupling mechanism, basics of circuit layout and grounding, concept of interfaces, filtering and shielding.
Safety: Introduction, electrical hazards, hazardous areas and classification, non-hazardous areas, enclosures – NEMA types, fuses and circuit breakers. Protection methods: Purging, explosion proofing and intrinsic safety.
L.D.Goettsche, “Maintenance of Instruments and Systems – Practical guides for measurements and control”, ISA, 1995.
CL 653 MODERN CONTROL SYSTEM
Examples, Building blocks of state space models, Canonical forms, State equation and its solution, Properties of the state transition matrix, Special cases, Modelling Discrete-time systems with delay operators.
Basic linear algebra, Eigenvalues and Eigenvectors, Similarity transformation, Gram-Schmidt Orthonormalization, Computing the matrix exponential using different algorithms, State transition matrix for discrete-time systems, Computational complexity.
Modelling energy of the system in terms of quadratic functions, Lyapunov’s criterion for continuous- and discrete-time systems, Numerical methods for solving the Lyapunov equation, Computational complexity.
Controllability & Observability
Definitions, Rank tests, Computational methods of determining rank, Computational complexity, Lyapunov equation and Grammians.
Design in State Space
State feedback control for controllable canonical form, State feedback control in general, State feedback for discrete-time systems, Computational algorithms and their complexity, Output feedback control. Full-order and reduced-order observers, Physical aspects of control system design in state space.
Ramakalyan, A., Control Engineering: A Comprehensive Foundation, Vikas Publishing House, New Delhi, 2003.
Ogata, K., Discrete-Time Control Systems, 2/e, Prentice Hall of India.
Datta, B.N., Numerical Methods for Linear Control Systems, Elsevier, 2004. (A cheaper Indian reprint is available)
CL 601 ADVANCED PROCESS CONTROL Review of Systems: Review of first and higher order systems, closed and open loop response. Response to step, impulse and sinusoidal disturbances. Transient response. Block diagrams.
Stability Analysis: Frequency response, design of control system, controller tuning and process identification. Zigler-Nichols and Cohen-Coon tuning methods, Bode and Nyquist stability criterion. Process identification.
Special Control Techniques: Advanced control techniques, cascade, ratio, feed forward, adaptive control, Smith predictor, internal model control.
Multivariable Control Analysis: Introduction to state-space methods, , Control degrees of freedom analysis and analysis, Interaction, Bristol arrays, Niederlinski index - design of controllers, Tuning of multivariable controllers.
Sample Data Controllers: Basic review of Z transforms, Response of discrete systems to various inputs. Open and closed loop response to step, impulse and sinusoidal inputs, closed loop response of discrete systems. Design of digital controllers. Introduction to PLC and DCS.
D.R. Coughanour, ‘Process Systems analysis and Control’, McGraw-Hill, 2nd Edition, 1991.
D.E. Seborg, T.F. Edger, and D.A. Millichamp, ‘Process Dynamics and Control’, John Wiley and Sons, 2nd Edition, 2004.
B.A.Ogunnaike and W.H.Ray, “Process Dynamics, Modelling and Control”, Oxford Press, 1994.
W.L.Luyben, ‘Process Modelling Simulation and Control for Chemical Engineers’, McGraw Hill, 2nd Edition, 1990.
B.W. Bequette, ‘Process Control: Modeling, Design and Simulation’, PHI, 2006.
S. Bhanot, ‘Process Control: Principles and Applications’, Oxford University Press, 2008.
CL 603 PROCESS MODELLING AND SIMULATION Introduction to modelling, a systematic approach to model building, classification of models. Conservation principles, thermodynamic principles of process systems.
Development of steady state and dynamic lumped and distributed parameter models based on first principles. Analysis of ill-conditioned systems.
Development of grey box models. Empirical model building. Statistical model calibration and validation. Population balance models. Examples.
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/SCILAB. Solution strategies for distributed parameter models. Solving parabolic, elliptic and hyperbolic partial differential equations. Finite element and finite volume methods.
K. M. Hangos and I. T. Cameron, “Process Modelling and Model Analysis”, Academic Press, 2001.
W.L. Luyben, “Process Modelling, Simulation and Control for Chemical Engineers”, 2nd Edn., McGraw Hill Book Co., New York, 1990.
W. F. Ramirez, “Computational Methods for Process Simulation”, Butterworths, 1995.
Mark E. Davis, “Numerical Methods and Modelling for Chemical Engineers”, John Wiley & Sons, 1984.
Singiresu S. Rao, “Applied Numerical Methods for Engineers and Scientists” Prentice Hall, Upper Saddle River, NJ, 2001