Title :
An improved Genetic Algorithm for multi-delay times identification
Author :
Yongfang, Xie ; Jing, Zhang ; Can, Huang ; Chunhua, Yang
Author_Institution :
Central South Univ. Inst. of Inf. Sci. & Eng., Changsha, China
Abstract :
An improved Genetic Algorithm(GA) is developed for solving the problem of multi-time delays identification in complex industrial processes. Such as Elitism, optimum selection crossover operate and cataclysmic mutation are adopted in the improved genetic algorthm, then applied to obtain an optimal multi-time delays identification of MIMO system. The simulation result shows that this improved GA´s result is more efficient in accuracy as well as in convergence.
Keywords :
MIMO systems; delays; genetic algorithms; MIMO system; cataclysmic mutation; complex industrial process; improved genetic algorithm; multidelay time identification; Control systems; Delay; Genetic algorithms; Genetics; MIMO; Optimization; Process control; Multi-time delays; improved genetic algorithm; parameter identification;
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
DOI :
10.1109/CCDC.2011.5968818
