Course

Introduction: Review of basics of Process Control, Control objective and benefits, Control system elements. Mathematical modeling and dynamic performance analysis process for control: Basic Concepts in modeling, models from fundamental laws, empirical model identification, dynamic performance analysis of first order, second order, multi-capacity processes, Effect of Zeros and time delay. Multivariable Process control: Cascade control, Ratio control, feedback-feed forward control, override control, selective control, modeling of multivariable process, Design of Multivariable controllers. Model Based control: Feedback-feed forward, delay compensation, Internal Model controller (IMC): Concept, IMC design Procedure. MPC: General Principles, Model forms, DMC, SISO unconstrained DMC Problem, controller tuning. Statistical Process Control (SPC): Concept, Design procedure.

Mini project: Design of Fuzzy-Logic based controller, Design of Neural Network based controller.

Textbooks/References:

1. Thomas Marlin, “Process Control”, McGraw-Hill International Edition.
2. Jose Romagnoli and Ahmet Palazoglu, “Introduction to Process Control”, CRC Taylor and Francis Group.
3. Statistical Process Control –ISA.
4. G. Liptak, “Handbook of Instrumentation – Process Control”.
5. Les Kane, “Handbook of Advanced Process Control Systems and Instrumentation”

Springer.