Study of IM Parameter Identification Using Multi-objective Particle Swarm Optimization with Proportional Guided Strategy

Authors

Huang Song, 1. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;;
Tian Na, 1. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;;
Wang Yan, 1. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;;
Zhicheng Ji, 1. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;;2. Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Wuxi 214122, China;

Abstract

Abstract: A multi-parameter and multi-objective identification model of induction motor was established, and a multi-objective particle swarm optimization based on Pareto set and all personal-best positions guided strategy was proposed and applied to the identification model. Not considerring the weighted coefficient of each objective, Pareto set is able to avoid subjective choice of the coefficients of multi-objective identification and proportion strategy with all personal-best positions guided could balance the learning ability from personal-best positions and global-best position. Having verified the performance on Matlab/Simulink, the results show that the proposed algorithm is able to improve parameter identification accuracy, and has a better performance.

Recommended Citation

Song, Huang; Na, Tian; Yan, Wang; and Ji, Zhicheng (2020) "Study of IM Parameter Identification Using Multi-objective Particle Swarm Optimization with Proportional Guided Strategy," Journal of System Simulation: Vol. 28: Iss. 7, Article 2.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss7/2

First Page

1489

Revised Date

2015-08-22

DOI Link

https://doi.org/

Last Page

1496

CLC

TP18;TM85

Recommended Citation

Huang Song, Tian Na, Wang Yan, Ji Zhicheng. Study of IM Parameter Identification Using Multi-objective Particle Swarm Optimization with Proportional Guided Strategy[J]. Journal of System Simulation, 2016, 28(7): 1489-1496.