Introduction - Intelligent Systems Control

Module 1 Lecture 1 Linear Neural networks

Module 1 Lecture 2 Multi layered neural networks

Module 1 lecture 3 Back Propagation Algorithm revisited

Module 1 lecture 4 Non linear system analysis Part 1

Module 1 lecture 5 non linear system analysis part 2

Module 1 lecture 6 Radial Basis function networks

Module 1 lecture 7 Adaptive learning rate

Module 1 Lecture 8 Weight update rules

Module 1 Lecture 8 Weight update rules

Mod 1 Lec 9 Recurrent networks Back propagation through time

Mod 1 Lec 10 Recurrent networks Real time recurrent learning

Mod 1 Lec 11 Self organizing Map - Multidimensional networks

Module 2 Lecture 1 Fuzzy sets A Primer

Module 2 Lecture 2 Fuzzy Relations

Module 2 lecture 3 Fuzzy Rule base and Approximate Reasoning

Module 2 lecture 3 Fuzzy Rule base and Approximate Reasoning

Module 2 Lecture 4 Introduction to Fuzzy Logic Control

Module 3 Lecture 1 Neural Control A review

Module 3 Lecture 2 Network inversion and Control

Module 3 Lecture 3 Neural Model of a Robot manipulator

Mod 3 Lec 4 Indirect Adaptive Control of a Robot manipulator

Mod 3 Lect 5 Adaptive neural control for Affine Systems SISO

Mod 3 Lec 6 Adaptive neural control for Affine systems MIMO

Module 3 Lecture 7 Visual Motor Coordination with KSOM

Mod 3 Lec 8 Visual Motor coordination - quantum clustering

Mod 3 Lec 9 Direct Adaptive control of Manipulators - Intro

Module 3 Lecture 10 NN based back stepping control

Module 4 lecture 1 Fuzzy Control - a Review

Mod 4 Lec 2 Mamdani type flc and parameter optimization

Module 4 Lecture 3 Fuzzy Control of a pH reactor

Mod 4 Lec 4 Fuzzy Lyapunov controller - Computing with words

IMod 4 Lect 5 Controller Design for a T-S Fuzzy model

Module 4 Lecture 6 Linear controllers using T-S fuzzy model