Intelligent Signal Processing for Active Control

Abstract

This research is concerned with the use of neural architectures and fuzzy expert systems in nonlinear system identification and in the control of such systems. In particular, on-line identification/modeling is considered. The research has resulted in a technique where the network can evolve (in size) in time-so as to provide an optimal model/controller. Also an adaptive algorithm, which is less sensitive to initial values of the weights and the learning rate, has been developed. We have also established a common framework between neural networks and fuzzy expert systems and developed a neuro-fuzzy architecture that retains the best of the two areas. The use of the architectures and the adaptation algorithm has been demonstrated on a number of applications.

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Document Details

Document Type
Technical Report
Publication Date
Jun 17, 1992
Accession Number
ADA252232

Entities

People

  • P. A. Ramamoorthy

Organizations

  • University of Cincinnati

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Complex Systems
  • Computers
  • Computing System Architectures
  • Content Addressable Memory
  • Control Systems
  • Engineering
  • Identification
  • Information Science
  • Linear Systems
  • Network Architecture
  • Neural Networks
  • Nonlinear Dynamics
  • Signal Processing
  • Systems Engineering

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

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