The model reference adaptive control based on the genetic algorithm

Author

Jia, Lei ; Jingping, Jiang

Author_Institution

Dept. of Electr. Eng., Zhejiang Univ., Hangzhou, China

Volume

2

fYear

1997

fDate

9-12 Jun 1997

Firstpage

783

Abstract

A control method that is a model reference adaptive control method (MRAC) based on the combination of PID control and the genetic algorithm is introduced. It implements the the genetic algorithm´s global optimization to optimize the PID´s three control parameters: Kp, Ki, Kd, to obtain the best control effect. This paper gives an example using this method to control a nonlinear system-continuous stirred tank reactor system (CSTR). Because the state of the CSTR system can not be obtained, a neural network is used to estimate the value of the state. This neural network is trained by the GA. Simulation results are given

Keywords

chemical technology; digital simulation; genetic algorithms; learning (artificial intelligence); model reference adaptive control systems; neural nets; nonlinear control systems; process control; state estimation; three-term control; CSTR; PID control; continuous stirred tank reactor system; genetic algorithm; global optimization; model reference adaptive control; nonlinear system; Adaptive control; Biological cells; Communication system control; Continuous-stirred tank reactor; Control systems; Encoding; Genetic algorithms; Neural networks; Nonlinear control systems; Three-term control;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks,1997., International Conference on

Conference_Location

Houston, TX

Print_ISBN

0-7803-4122-8

Type

conf

DOI

10.1109/ICNN.1997.616122

Filename

616122