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A decoupling control of composite cage rotor bearingless induction motor based on SA-PSO support vector machine inverse
International Transactions on Electrical Energy Systems ( IF 1.9 ) Pub Date : 2021-06-28 , DOI: 10.1002/2050-7038.12988
Chengling Lu 1 , Zebin Yang 1 , Xiaodong Sun 2 , Qifeng Ding 1 , Qian Zhao 1
Affiliation  

A composite cage rotor bearingless induction motor (CCR-BIM) is a complicated system with multi-variable, nonlinear, and strong coupling. The decoupling control among speed and flux linkage and radial displacement is the base of the stable operation based on the structure, the suspension force and the mathematical model of the CCR-BIM. A decoupling control strategy based on simulated annealing particle swarm optimization (SA-PSO) support vector machine (SVM) inverse is proposed for the CCR-BIM. First, the state equation and reversibility of the system are analyzed using a CCR-BIM mathematical model and a compounded pseudo-linear system consisting of the inverse system constructed is decoupled into two displacement subsystems by nonlinear SVM in series with the original system, a speed subsystem, and a flux linkage subsystem. Second, the SA-PSO is introduced to improve the precision of the prediction model. Finally, results of simulation and experimental verify that the proposed strategy not only achieves the decoupling control between the speed, radial displacement and flux linkage, but also achieves stable suspension and high performance of the CCR-BIM.

中文翻译:

基于SA-PSO支持向量机逆的复合笼型转子无轴承异步电动机解耦控制

复合笼式转子无轴承感应电动机(CCR-BIM)是一个具有多变量、非线性和强耦合的复杂系统。基于CCR-BIM的结构、悬架力和数学模型,速度与磁链、径向位移的解耦控制是稳定运行的基础。针对CCR-BIM,提出了一种基于模拟退火粒子群优化(SA-PSO)支持向量机(SVM)逆的解耦控制策略。首先,利用CCR-BIM数学模型分析系统的状态方程和可逆性,并通过非线性SVM与原系统串联,将构建的逆系统组成的复合伪线性系统解耦为两个位移子系统,一个速度子系统和磁链子系统。第二,引入 SA-PSO 以提高预测模型的精度。最后,仿真和实验结果验证了所提出的策略不仅实现了速度、径向位移和磁链之间的解耦控制,而且实现了CCR-BIM的稳定悬挂和高性能。
更新日期:2021-08-07
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