采用改进遗传算法优化LS-SVM逆系统的外转子无铁心无轴承永磁同步发电机解耦控制

Decoupling Control of Outer Rotor Coreless Bearingless Permanent Magnet Synchronous Generator Using LS-SVM Inverse System Optimized by the Improved Genetic Algorithm

为了实现外转子无铁心无轴承永磁同步发电机(outer rotor coreless bearingless permanent magnet synchronous generator,ORC-BPMSG)的精确控制,提出一种基于改进遗传算法(improved genetic algorithm,IGA)优化最小二乘支持向量机(least square support vector machine,LS-SVM)逆系统的解耦控制策略。首先,基于ORC-BPMSG的结构及工作原理,推导其数学模型,并分析其可逆性。其次,建立LS-SVM回归方程,并采用IGA优化LS-SVM的性能参数,从而训练得到逆系统。然后,将逆系统与原系统串接,形成伪线性系统,实现了ORC-BPMSG的线性化和解耦。最后,将提出的控制方法与传统LS-SVM逆系统控制方法进行对比仿真和实验。仿真和实验结果表明:所提出的控制策略可以较好地实现ORC-BPMSG输出电压和悬浮力、以及悬浮力之间的解耦控制。

In order to realize the precise control of the outer rotor coreless bearingless permanent magnet synchronous generator(ORC-BPMSG),a decoupling control strategy of ORC-BPMSG based on the least squares support vector machine(LS-SVM) inverse system optimized by the improved genetic algorithm(IGA) is proposed.First,based on the structure and working principle of the ORC-BPMSG,its mathematical model is deduced,and its reversibility is analyzed.Second,the LS-SVM regression equation is established,and IGA is used to optimize the performance parameters of LS-SVM,so as to train the inverse system.Then,the inverse system is concatenated with the original system to form a pseudo-linear system,which realizes the linearization and decoupling of the ORC-BPMSG.Finally,the proposed control method is compared with the traditional LS-SVM inverse system control method for simulation and experiments.The simulation and experimental results show that the proposed control strategy can better achieve the decoupling control among output voltage and suspension forces,as well as the decoupling control between the suspension forces of the ORC-BPMSG.