An intelligent control system based on multiobjective genetic algorithms and fuzzy neural network

Liang-Hsuan Chen, Cheng Hsiung Chiang

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

A novel approach to intelligent control systems is proposed. It has three main functions: the fuzzy neural network controller, the performance evaluator, and the decision maker, which is to explore new actions to enhance control performance. The multiobjective genetic algorithm is presented to implement the adaptive mechanism to explore the new actions. The simulation results of robotic path planning showed the robot could reach the target point without collisions in various environments.

Original languageEnglish
Pages (from-to)262-267
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume3
Publication statusPublished - 2002 Dec 1
Event2002 IEEE International Conference on Systems, Man and Cybernetics - Yasmine Hammamet, Tunisia
Duration: 2002 Oct 62002 Oct 9

Fingerprint

Fuzzy neural networks
Intelligent control
Motion planning
Robotics
Genetic algorithms
Robots
Control systems
Controllers

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Hardware and Architecture

Cite this

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