DocumentCode :
7983
Title :
Coevolutionary Particle Swarm Optimization Using AIS and its Application in Multiparameter Estimation of PMSM
Author :
Zhao-Hua Liu ; Jing Zhang ; Shao-Wu Zhou ; Xiao-Hua Li ; Kan Liu
Author_Institution :
Sch. of Inf. & Electr. Eng., Hunan Univ. of Sci. & Technol., Xiangtan, China
Volume :
43
Issue :
6
fYear :
2013
fDate :
Dec. 2013
Firstpage :
1921
Lastpage :
1935
Abstract :
In this paper, a coevolutionary particle-swarm-optimization (PSO) algorithm associating with the artificial immune principle is proposed. In the proposed algorithm, the whole population is divided into two kinds of subpopulations consisting of one elite subpopulation and several normal subpopulations. The best individual of each normal subpopulation will be memorized into the elite subpopulation during the evolution process. A hybrid method, which creates new individuals by using three different operators, is presented to ensure the diversity of all the subpopulations. Furthermore, a simple adaptive wavelet learning operator is utilized for accelerating the convergence speed of the pbest particles. The improved immune-clonal-selection operator is employed for optimizing the elite subpopulation, while the migration scheme is employed for the information exchange between elite subpopulation and normal subpopulations. The performance of the proposed algorithm is verified by testing on a suite of standard benchmark functions, which shows faster convergence and global search ability. Its performance is further evaluated by its application to multiparameter estimation of permanent-magnet synchronous machines, which shows that its performance significantly outperforms existing PSOs. The proposed algorithm can estimate the machine dq-axis inductances, stator winding resistance, and rotor flux linkage simultaneously.
Keywords :
parameter estimation; particle swarm optimisation; permanent magnet machines; rotors; stators; synchronous machines; wavelet transforms; AIS; PMSM; artificial immune principle; coevolutionary particle-swarm-optimization; elite subpopulation; global search ability; immune-clonal-selection operator; machine dq-axis inductances; multiparameter estimation; normal subpopulations; permanent-magnet synchronous machines; rotor flux linkage; simple adaptive wavelet learning operator; standard benchmark functions; stator winding resistance; Immune systems; Parameter estimation; Particle swarm optimization; Permanent magnet machines; Artificial immune system (AIS); coevolution; elite population; global search; migration scheme; parameter estimation; particle swarm optimization (PSO); permanent-magnet synchronous machines (PMSMs);
fLanguage :
English
Journal_Title :
Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
2168-2267
Type :
jour
DOI :
10.1109/TSMCB.2012.2235828
Filename :
6494272
Link To Document :
بازگشت