Title :
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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.259109
