Intelligent Control

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INTELLIGENT CONTROL 2730703
FREE PDF 2730703
Code: 2730703 Credits: 5 Semester 3 EE

Intelligent Control

Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.

Intelligent Control Syllabus — Unit-wise Content

The official GTU curriculum for Intelligent Control (subject code 2730703) as prescribed for EE · Semester 3 divides the course into 4 units, covering 31 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.

Download the official syllabus PDF (2730703)

Unit 1 UNIT I

9 lecture hours

  • INTRODUCTION Approaches to intelligent control
  • Architecture for intelligent control
  • Symbolic reasoning system
  • rule-based systems
  • the AI approach
  • Knowledge representation
  • Expert systems

Unit 2 UNIT II

9 lecture hours

  • ARTIFICIAL NEURAL NETWORKS 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 3 UNIT III

9 lecture hours

  • GENETIC ALGORITHM 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 4 UNIT IV

9 lecture hours

  • FUZZY LOGIC SYSTEM Introduction to crisp sets and fuzzy sets
  • basic fuzzy set operation and approximate reasoning
  • Introduction to fuzzy logic modeling and control
  • inferencing and defuzzification
  • Fuzzy knowledge and rule bases
  • Fuzzy modeling and control schemes for nonlinear systems
  • Self- organizing fuzzy logic control
  • Fuzzy logic control for nonlinear time-

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