Application of genetic algorithm to decentralized control of robot manipulators

Author

Miryazdi, Hamid Reza ; Khaloozadeh, Hamid

Author_Institution

Dept. of Electr. Eng., Ferdowsi Univ. of Mashhad, Iran

fYear

2002

fDate

2002

Firstpage

334

Lastpage

339

Abstract

This paper discusses the genetic algorithm to improve a decentralized adaptive control scheme to reduce tracking errors of robot manipulators. A simple PD conventional controller is used together with a cubic feedback and adaptive controller to ensure its global stability. A genetic algorithm is then proposed to determine the coefficients of the PD, nonlinear and adaptive controller such that the tracking errors of the robot, that is fitness function of genetic algorithm, are minimized. In order to show the performance of the proposed method, computer simulations are implemented on a simple two link robot manipulator.

Keywords

adaptive control; decentralised control; genetic algorithms; manipulator dynamics; nonlinear control systems; stability; tracking; two-term control; PD controller; adaptive control; decentralized control; genetic algorithm; global stability; nonlinear control system; tracking errors; trajectory tracking; two link manipulator; Adaptive control; Distributed control; Error correction; Feedback; Genetic algorithms; Manipulators; PD control; Programmable control; Robots; Stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence Systems, 2002. (ICAIS 2002). 2002 IEEE International Conference on

Print_ISBN

0-7695-1733-1

Type

conf

DOI

10.1109/ICAIS.2002.1048123

Filename

1048123