Intelligent Fuzzy Controller for Satellite Ground Station Applications

Abstract

The Department of Computer Science at Clark Atlanta University investigated the use of genetic algorithms as a technique for automating the development of fuzzy logic controllers. The derivation of fuzzy controller rule-bases is relatively straightforward; however, the tuning of these controllers is a difficult process. In the first phase of this research, a genetic algorithm was used to tune the fuzzy controller. The genetic algorithm searches through the space of all membership functions to select the functions that produce the best control action. In the second phase of this project, the genetic algorithm was used to automatically derive the rule-base and membership functions. A full-featured research prototype was developed. The methodology and prototype were validated on typical control and classification problems. This research establishes a methodology for the rapid development of robust knowledge-based control systems in complex, poorly understood domains.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1997
Accession Number
ADA332642

Entities

People

  • Roy George

Organizations

  • Clark Atlanta University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Artificial Satellites
  • Classification
  • Computer Science
  • Computers
  • Control Systems
  • Control Systems Engineering
  • Fuzzy Logic
  • Genetic Algorithms
  • Ground Stations
  • Models
  • Neural Networks
  • Prototypes
  • Software Development
  • Space Systems
  • Two Dimensional

Readers

  • Artificial Intelligence
  • Database Systems and Applications
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Biotechnology
  • Space
  • Space - Spacecraft Maneuvers