Speed Control of Switched Reluctance Motor Using New Hybrid Particle Swarm Optimization | Science Publications

Journal of Computer Science

P. Thangam¹  K. Thanushkodi¹  T. V. Mahendiran¹ 

关键词: Switched reluctance motor;    differential evolution;    Particle Swarm Optimization (PSO);    fuzzy logic controller;    fuzzy PI controller;    PWM inverter;   

DOI  :  10.3844/jcssp.2012.1473.1477

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

Problem statement: The main objective of this research is to obtain the speed control of switched reluctance motor with minimum settling time and without overshoot. Approach: A new algorithm has been developed with the combination of differential evolution and particle swarm optimization and applied for speed control of switched reluctance motor under sudden change in speed. Also speed control of switched reluctance motor was obtained by other artificial intelligence methods such as fuzzy logic controller, fuzzy PI controller and particle swarm optimization based tuning of fuzzy PI controller. Matlab/Simulink environment was used for the simulation. Results: Results are discussed and tabulated based on the performance of the controllers. Conclusion: From the comparison of all above methods, the algorithm has given better results in speed response than other controllers.

【 授权许可】

Unknown