Design of an adaptive fuzzy logic controller

Author

Pham, D.T. ; Karaboga, D.

Author_Institution

Intelligent Syst. Res. Lab., Univ. of Wales Coll. of Cardiff, UK

Volume

1

fYear

1994

fDate

2-5 Oct 1994

Firstpage

437

Abstract

This paper proposes an adaptive fuzzy logic controller based on the structure of the self-tuning regulator and neural network and genetic algorithm techniques. The system has two main functions: online process identification and fuzzy logic controller modification using the identified model. A recurrent neural network performs the identification and a genetic algorithm obtains the best process model and evolves the best controller design. The paper presents simulation results to show the effectiveness of the proposed system

Keywords

adaptive control; control system synthesis; fuzzy control; genetic algorithms; neurocontrollers; recurrent neural nets; adaptive fuzzy logic controller; controller design evolution; fuzzy logic controller modification; genetic algorithm; neural network; online process identification; recurrent neural network; self-tuning regulator; Adaptive control; Control systems; Fuzzy control; Fuzzy logic; Genetic algorithms; Intelligent systems; Neural networks; Neurons; Programmable control; Recurrent neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on

Conference_Location

San Antonio, TX

Print_ISBN

0-7803-2129-4

Type

conf

DOI

10.1109/ICSMC.1994.399878

Filename

399878