The Optimal Composite Design Based on Genetic Algorithms for Non-Minimum Phase System

Author

Sun, Jian-ping ; Jin, Xiu-zhang

Author_Institution

Autom. Dept., North China Electr. Power Univ., Baoding

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

433

Lastpage

437

Abstract

The genetic algorithms (GAs) are used to optimize design for a non-minimum phase (NMP) system with time delay. The intelligent composite control strategy can effectively eliminate the overshoot and undershoot of a NMP system. In order to guarantee the smooth switch of the control modes, the fuzzy inference and optimization are imported. The simulation results show that the performance of control system based on optimal composite design is better than that of the FID control system

Keywords

control system synthesis; delays; fuzzy control; fuzzy reasoning; fuzzy set theory; genetic algorithms; intelligent control; large-scale systems; optimal control; GA; NMP system; fuzzy controller; fuzzy inference; fuzzy sets; genetic algorithms; intelligent composite control; nonminimum phase system; optimal composite design; optimization; time delay; Algorithm design and analysis; Control system synthesis; Control systems; Delay effects; Design optimization; Fuzzy control; Genetic algorithms; Intelligent control; Optimal control; Switches; Fuzzy optimal control; Genetic algorithms; Non-minimum phase system with time delay;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.259109

Filename

4028103