Monday, June 18, 2012
EE2025 INTELLIGENT CONTROL Syllabus | EEE |Anna University | Regulation 2008 | (Applicable to the students admitted from the Academic year 2008 – 2009 onwards)
EE2025 INTELLIGENT CONTROL L T P C
3 0 0 3
UNIT I INTRODUCTION 9
Approaches to intelligent control. Architecture for
intelligent control. Symbolic reasoning system,
rule-based systems, the AI approach. Knowledge
representation. Expert systems.
UNIT II ARTIFICIAL NEURAL NETWORKS 9
Concept of Artificial Neural Networks and its basic
mathematical model, McCulloch-Pitts neuron
model, simple perceptron, Adaline and Madaline,
Feed-forward Multilayer Perceptron. Learning and
Training the neural network. Data Processing: Scaling,
Fourier transformation, principal-component
analysis and wavelet transformations. Hopfield network,
Self-organizing network and Recurrent
network. Neural Network based controller
UNIT III GENETIC ALGORITHM 9
Basic concept of Genetic algorithm and detail algorithmic
steps, adjustment of free parameters.
Solution of typical control problems using genetic
algorithm. Concept on some other search
techniques like tabu search and ant-colony search
techniques for solving optimization problems.
UNIT IV FUZZY LOGIC SYSTEM 9
Introduction to crisp sets and fuzzy sets, basic fuzzy
set operation and approximate reasoning.
Introduction to fuzzy logic modeling and control.
Fuzzification, inferencing and defuzzification. Fuzzy
knowledge and rule bases. Fuzzy modeling and control
schemes for nonlinear systems. Selforganizing
fuzzy logic control. Fuzzy logic control for nonlinear
time-delay system.
97
UNIT V APPLICATIONS 9
GA application to power system optimisation problem, Case
studies: Identification and control of
linear and nonlinear dynamic systems using Matlab-Neural
Network toolbox.
Stability analysis of Neural-Network interconnection
systems. Implementation of fuzzy logic controller
using Matlab fuzzy-logic toolbox. Stability analysis of
fuzzy control systems.
TOTAL : 45 PERIODS TEXT BOOKS
1. Padhy.N.P.(2005), Artificial Intelligence and
Intelligent System, Oxford University Press.
2. KOSKO,B. "Neural Networks And Fuzzy
Systems", Prentice-Hall of India Pvt. Ltd., 1994.
REFERENCES
1. Jacek.M.Zurada, "Introduction to Artificial
Neural Systems", Jaico Publishing House, 1999.
2. KLIR G.J. & FOLGER T.A. "Fuzzy sets,
uncertainty and Information", Prentice-Hall of India Pvt.
Ltd., 1993.
3. Zimmerman H.J. "Fuzzy set theory-and its
Applications"-Kluwer Academic Publishers, 1994.
4. Driankov, Hellendroon, "Introduction to Fuzzy
Control", Narosa Publishers.
5. Goldberg D.E. (1989) Genetic algorithms in Search,
Optimization and Machine
learning,
Addison Wesley.
By Vinoth
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