TIEE3031 Syllabus - Computer Control Of Processes - 2022 Regulation Anna University

TIEE3031 Syllabus - Computer Control Of Processes - 2022 Regulation Anna University

TIEE3031	COMPUTER CONTROL OF PROCESSES	L T P C

3003

COURSE OBJECTIVES:

• To represent the linear time invariant System in discrete State Space form
• To analyze the controllability, observability and stability of a Discrete time System.
• To estimate model parameters from input/output measurements
• To Design Digital Controllers
• To Design Multi-loop and Multivariable Controllers for multivariable system

UNIT I	DISCRETE STATE-VARIABLE TECHNIQUE	(7+2 SKILL)9

State equation of discrete data system with sample and hold – State transition equation – Methods of computing the state transition matrix – Decomposition of discrete data transfer functions – State diagrams of discrete data systems – System with zero-order hold – Controllability and observability of linear time invariant discrete data system–Stability tests of discrete-data system.

UNIT II	SYSTEM IDENTIFICATION	(7+2 SKILL)9

Identification of Non-Parametric Input-Output Models: -Transient analysis–Frequency analysis– Correlation analysis– Spectral analysis – Identification of Parametric Input-Output Models: - Least Squares Method – Recursive Least Square Method.

UNIT III	DIGITAL CONTROLLER DESIGN	(7+2 SKILL)9

Review of z-transform – Modified of z-transform – Pulse transfer function – Digital PID controller – Dead-beat controller and Dahlin’s controller – Kalman’s algorithm, Pole Placement Controller

UNIT IV	MULTI-LOOP REGULATORY CONTROL	(7+2 SKILL)9

Multi-loop Control - Introduction – Process Interaction – Pairing of Inputs and Outputs -The Relative Gain Array (RGA) – Properties and Application of RGA - Multi-loop PID Controller – Biggest Log Modulus Tuning Method – De-coupler.

UNIT V	MULTIVARIABLE REGULATORY CONTROL	(7+2 SKILL)9

Introduction to Multivariable control –Multivariable PID Controller – Multivariable Dynamic Matrix Controller – Case Studies: - Distillation Column, CSTR and Four-tank system.

TOTAL: 45 PERIODS

COURSE OUTCOMES:

CO1 Develop mathematical models for discrete time systems using state variable techniques and analyze the stability of the systems. L4
CO2 Construct models from input-output data by least square and recursive least square method. L5
CO3 Ability to design different digital controllers to satisfy the required criterion. L5
CO4 Design a multi-loop controller and multivariable controller for multi-variable systems. L5
CO5 Ability to design multivariable dynamic matrix controller for industrial processes. L5

TEXT BOOKS:

1. Stephanopoulos, G., “Chemical Process Control -An Introduction to Theory and Practice”, Prentice Hall of India, 1st Edition, 2015.
2. Sigurd Skogestad, Ian Postlethwaite, “Multivariable Feedback Control: Analysis and Design”, John Wiley and Sons, 2005, 2nd Edition.

REFERENCES:

1. Thomas E. Marlin, Process Control – Designing Processes and Control systems for Dynamic Performance, Mc-Graw-Hill,2000, 2nd Edition.
2. Gopal, M., “Digital Control and State Variable Methods”, Tata Mc Graw Hill, 4th Edition, 2017.
3. P. Albertos and A. Sala, “Multivariable Control Systems An Engineering Approach”, Springer Verlag, 1st Edition, 2004
4. Bequette, B.W., “Process Control Modeling, Design and Simulation”, Prentice Hall of India, 1st Edition, 2003.
5. Dale E. Seborg, Duncan A. Mellichamp, Thomas F. Edgar, “Process Dynamics and Control”, Wiley John and Sons, 4th Edition, 2016.