PEI 105 PROCESS MODELING AND CONTROL



L 
T 
P 
Cr 

3 
1 
0 
3.5 
Prerequisite(s): None 
Course Objectives: To understand the concepts of process model and control, to enable to develop model and simulation of process control
Static and Dynamic characteristics: Dynamic analysis of instrumentation system, Relative merits of analytical and experimental modeling of dynamic behavior, Response system to step, Pulse, Harmonic and random test signals, Frequency spectra, Auto correlation spectral density, Loading effects under static and dynamic conditions.
Simulation and Modeling: Importance of simulation, Terms used Simulation, Mathematical modeling, Process dynamics of fluid flow and heat transfer systems, Mass transfer dynamics and distillation column, Reaction kinetics of chemical processes. Modeling of chemical processes like CSTR, single tank / multitank system and Distillation column, study the behaviour of above mentioned systems for various test signals , analysis of PID controller response.
Advanced Control Schemes: Structure, analysis and application of Cascade control, Selective control, Ratio Control, Design of steady state and dynamic feed forward controller, Feed forward combined with feedback control, Structure, analysis and applications of inferential control, Dead time and inverse response compensators, Concepts and applications of Adaptive control, Model reference adaptive control, Self tuning regulator.
Design of Multiloop Controllers: Interactions and decoupling of control loops. Design of cross controllers and selection of loops using Relative Gain Array (RGA).
Digital Control : Sampling and reconstruction, Transform analysis of sampleddata systems: ztransform and its evaluation, Inverse ztransform, Theorems of ztransform, Modified ztransform, Mapping of jplane to zplane, Pulse transfer function, Stability analysis in zplane, Mapping approximation of ztransform, Numerical solution of differential equations, Implementation of digital controller, Case studies.
Discrete Event System Modeling: Introduction to various methods of modeling, Automata Theory, Introduction to Petri Nets.
State Space Analysis: State space representation of continuous and discrete time control systems, Converting a continuous and discrete time system into its state space equivalent using MATLAB, Control theory, State space concepts, State variables, Pole placement design and state observes, Controllability and Observability of linear time invariant systems and the relation between them.Stability analysis, Definition, First and second method of Liapunov, Stability analysis of linear systems.
Course Outcomes: After the completion of this course the student will be able to:
understand the fundaments and overview of process control
understand the static and Dynamic analysis of instrumentation system
understand the concept of Simulation and Modeling
understand the Advanced Control Schemes
understand the Design of Multiloop Controllers and Digital controller and to study Discrete Event System Modeling
analyse the system through State Space Analysis, its Controllability and Observability and Stability Analysis
study Real Time Control strategies
Recommended Books
Bequette, B.W., Process Control: Modeling, Design And Simulation Prentice Hall of India (2003).
Harriott, P., Process Control, Tata McGraw Hill (2002).
Luyben, E., Essentials of Process Control, Tata McGraw Hill (1989).