IC1403 NEURAL NETWORK AND FUZZY LOGIC CONTROL PPT

1. ARCHITECTURES 9

Introduction –Biological neuron – Artificial neuron – Neuron modeling – Learning rules – Single layer – Multi layer feed forward network – Back propagation – Learningfactors.

2. NEURAL NETWORKS FOR CONTROL 9

Feed back networks – Discrete time hop field networks – Transient response of continuoustime networks – Applications of artificial neural network - Processidentification – Neuro controller for inverted pendulum.

3. FUZZY SYSTEMS 9

Classical sets – Fuzzy sets – Fuzzy relations – Fuzzification – Defuzzification – Fuzzy rules.

4. FUZZY LOGIC CONTROL 9

Membership function – Knowledge base – Decision-making logic – Optimisation of membership function using neural networks – Adaptivefuzzy system – Introduction to genetic algorithm.

5. APPLICATION OF FLC 9

Fuzzy logic control – Inverted pendulum – Image processing – Home heating system – Bloodpressure during anesthesia – Introduction to neuro fuzzy controller.

TEXT BOOKS

1. Jacek M. Zurada, ‘Introduction to Artificial Neural Systems’, Jaico Publishing home, 2002.

2. Timothy J. Ross, ‘Fuzzy Logic with Engineering Applications’, Tata McGraw Hill, 1997.

REFERENCE BOOKS

1. Laurance Fausett, Englewood cliffs, N.J., ‘Fundamentals of Neural Networks’, Pearson Education, 1992.

2. H.J. Zimmermann, ‘Fuzzy Set Theory & its Applications’, Allied Publication Ltd., 1996.

3. Simon Haykin, ‘Neural Networks’, Pearson Education, 2003.

4. John Yen & Reza Langari, ‘Fuzzy Logic – Intelligence Control & Information’, Pearson

Education, New Delhi, 2003.

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