Particle Swarm Optimization Based Continuous Control Set Model Predictive Speed Control for PMSM

被引:0
|
作者
Kong, Xiangzhou [1 ,2 ]
Li, Jiaxiang [2 ,3 ]
Li, Zheng [2 ]
Du, Jianming [4 ]
Yang, Yumin [3 ]
Wang, Fengxiang [2 ]
Rodriguez, Jose [5 ]
机构
[1] Northeastern Univ, Coll Engn, Boston, MA 02115 USA
[2] Chinese Acad Sci, Natl & Local Joint Engn Res Ctr Elect Drives & Po, Quanzhou Inst Equipment Mfg, Haixi Inst, Quanzhou, Peoples R China
[3] Fuzhou Univ, Coll Elect Engn & Automat, Fuzhou, Peoples R China
[4] Munich Univ Appl Sci, Munich, Germany
[5] Univ Andres Bello, Santiago, Chile
关键词
continuous control set model predictive control (CCS-MPC); particle swarm optimization (PSO); permanent magnet synchronous motor (PMSM);
D O I
10.1109/PRECEDE51386.2021.9680924
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A continuous control set model predictive speed control (CCS-MPSC) strategy based on the particle swarm optimization (PSO) algorithm is proposed, where the cost function of model predictive speed control (MPSC) is regarded as the objective function to evaluate the fitness of the particles. During this process, all particles are ordered to conduct optimization under the hexagonal sector composed of voltage space vectors. At the end, the particles coverage to the optimal value through keeping updating particle positions. As the feedback, the system obtains the optimal voltage vector without the derivation of error model and realizes CCS-MPSC. According to the simulation results, the effectiveness, and the robustness of speed control with mutative work conditions.
引用
收藏
页码:152 / 156
页数:5
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