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Intelligent Systems and Control

Intelligent Systems and Control. Instructor: Prof. Laxmidhar Behera, Department of Electrical Engineering, IIT Kanpur. This course provides an introduction to the basics of intelligent systems and control. Topics covered include: artificial neural networks, backpropagation networks, radial basis function networks, recurrent networks, fuzzy logic, fuzzy and expert control, fuzzy neural networks, adaptive control using neural and fuzzy neural networks, applications to pH reactor control, flight control, and robot manipulator dynamic control. (from nptel.ac.in)

Lecture 25 - Direct Adaptive Control of Manipulators: Introduction


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Lecture 01 - Introduction to Intelligent Systems and Control
Lecture 02 - Linear Neural Networks
Lecture 03 - Multilayered Neural Networks
Lecture 04 - Backpropagation Algorithm Revisited
Lecture 05 - Nonlinear System Analysis, Part I
Lecture 06 - Nonlinear System Analysis, Part II
Lecture 07 - Radial Basis Function Networks
Lecture 08 - Adaptive Learning Rate
Lecture 09 - Weight Update Rules
Lecture 10 - Recurrent Networks: Backpropagation through Time
Lecture 11 - Recurrent Networks: Real Time Recurrent Learning
Lecture 12 - Self Organizing Map - Multidimensional Networks
Lecture 13 - Fuzzy Sets - A Primer
Lecture 14 - Fuzzy Relations
Lecture 15 - Fuzzy Rule Base and Approximate Reasoning
Lecture 16 - Introduction to Fuzzy Logic Control
Lecture 17 - Neural Control - A Review
Lecture 18 - Neural Inversion and Control
Lecture 19 - Neural Model of a Robot Manipulator
Lecture 20 - Indirect Adaptive Control of a Robot Manipulator
Lecture 21 - Adaptive Neural Control for Affine Systems SISO
Lecture 22 - Adaptive Neural Control for Affine Systems MIMO
Lecture 23 - Visual Motor Coordination with KSOM
Lecture 24 - Visual Motor Coordination - Quantum Clustering
Lecture 25 - Direct Adaptive Control of Manipulators: Introduction
Lecture 26 - NN based Backstepping Control
Lecture 27 - Fuzzy Control - A Review
Lecture 28 - Mamdani Type FLC and Parameter Optimization
Lecture 29 - Fuzzy Control of a pH Reactor
Lecture 30 - Fuzzy Lyapunov Controller - Computing with Words
Lecture 31 - Controller Design for a Takagi-Sugeno Fuzzy Model
Lecture 32 - Linear Controllers using Takagi-Sugeno Fuzzy Model