DocumentCode :
2781732
Title :
Optimization of PID parameters based on genetic algorithm and interval algorithm
Author :
Shao Xiao-Gen ; Xiao Li-Qing ; Han Cheng-Chun
Author_Institution :
Xuzhou Inst. of Technol., Xuzhou, China
fYear :
2009
fDate :
17-19 June 2009
Firstpage :
741
Lastpage :
745
Abstract :
To overcome simple genetic algorithm´s defects of worse local searching ability and premature convergence, a hybrid algorithm of genetic algorithm and interval algorithm was proposed, and applied to parameters optimization of PID controller by employing interval algorithm in population initialization of genetic algorithm. The simulation and experimental results show that the new algorithm is better than simple genetic algorithm, which can improve the convergence speed, overcome the premature convergence phenomena, reduce the influence of random initial population, improve the convergence precision, and has excellent convergence performance and optimization ability.
Keywords :
genetic algorithms; three-term control; PID controller; PID parameters; convergence speed; genetic algorithm; interval algorithm; parameters optimization; premature convergence phenomena; worse local searching ability; Biological cells; Control system synthesis; Convergence; Electronic mail; Evolution (biology); Evolutionary computation; Genetic algorithms; Genetic mutations; Robust control; Three-term control; Genetic Algorithm; Interval Algorithm; PID Controller; Simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
Type :
conf
DOI :
10.1109/CCDC.2009.5191861
Filename :
5191861
Link To Document :
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