Title :
A Hybrid Particle Swarm Algorithm for Nonlinear Parameter Estimation
Author :
Pei, Shengyu ; Zhou, Yongquan ; Luo, Qifang
Author_Institution :
Coll. of Math. & Comput. Sci., Guangxi Univ. for Nat., Nanning, China
Abstract :
A hybrid particle swarm optimization algorithm for solving non-linear parameter estimation is proposed, which is based on genetic algorithm. And can increase the diversity of population and make the particles have a definite evolution direction when they are renewed. This improved approach has been tested on some problems commonly used in this paper. The results show that the proposed approach is an efficient and can reach a higher precision.
Keywords :
genetic algorithms; nonlinear estimation; parameter estimation; particle swarm optimisation; crossover operator; evolution direction; genetic algorithm; hybrid particle swarm optimization algorithm; nonlinear parameter estimation; Automation; Computer science; Control theory; Educational institutions; Genetic algorithms; Mathematics; Optimization methods; Parameter estimation; Particle swarm optimization; Three-term control; crossover operator; genetic algorithm; parameters estimation; particle swarm optimization;
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
DOI :
10.1109/ICICTA.2009.61
