Application of Artificial Neural Networks in the Design of Control Systems

Abstract

The paper develops important fundamental steps in applying artificial neural networks in the design of intelligent control systems. Different architectures including single layered and multi layered of neural networks are examined for controls applications. The importance of different learning algorithms for both linear and nonlinear neural networks is discussed. The problem of generalization of the neural networks in control systems together with some possible solutions are also included.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2000
Accession Number
ADA384438

Entities

People

  • B. G. Sherlock
  • Hong H. Mu
  • Y. P. Kakad

Organizations

  • University of North Carolina at Charlotte

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Computers
  • Computing System Architectures
  • Control Systems
  • Data Analysis
  • Data Sets
  • Differential Equations
  • Equations
  • Information Science
  • Interdisciplinary Science
  • Learning
  • Least Squares Method
  • Mathematical Models
  • Models
  • Network Architecture
  • Neural Networks
  • Training

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Cybersecurity.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks