Course Details

Subject {L-T-P / C} : EE6351 : Intelligent Control {3-0-0 / 3}
Subject Nature : Theory
Coordinator : Prof. Bidyadhar Subudhi


Artificial Neural Networks Applications to System Identification & Control: Introduction, learning with ANNs, single-layer networks, multi-layer perceptrons, ANNs for identification, ANNs for control. Fuzzy Logic Control: Introduction, fuzzy sets, fuzzy logic, fuzzy logic controller design, Fuzzy Modelling& identification, Adaptive Fuzzy Control Design. Evolutionary Computation for Control & identification: Applications of EC methods to system identification and control. Combination of Soft Computation Approaches Control & Identification: Neuro-fuzzy, evolutionary neuro and evolutionary fuzzy systems

Course Objectives

  1. To understand about different soft computing techniques such as neural network, fuzzy logic and evolutionary techniques for designing intelligent controllers
  2. To design Intelligent controllers such fuzzy controller, neuro controller and evolutionary controllers
  3. To pursue stability analysis of intelligent controllers

Course Outcomes

CO1: Gaining an understanding of the functional operation of a variety of intelligent control techniques and their bio-foundations,
CO2: Learning analytical approaches to study properties (especially stability analysis), and use of the computer for simulation and evaluation.

Essential Reading

  1. Rojer Jang, Soft Computing, PHI
  2. D Driankov, H Hellendoorn and M Reinfrank, n Introduction to Fuzzy Control, Springer-Verlag, 2001.

Supplementary Reading

  1. K. Passino, Biomimicry for Optimization, Control, and Automation, Springer-Verlag, London, UK, 2005
  2. S.H. Zak, Systems and Control, Oxford