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32
Sessions

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Course Description

Intelligent control is a class of control techniques that use various artificial intelligence computing approaches like neural networks, Bayesian probability, fuzzy logic, machine learning, evolutionary computation and genetic algorithms.

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Course Syllabus
  • 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
  • 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 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
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