基于在线粒子群优化方法的IPMSM驱动电流和速度控制器
Current and speed controllers driven by IPMSM based on online particle swarm optimization method

摘要： 利用在线粒子群优化方法(particle swarm optimization, PSO)设计内埋式永磁同步电动机(interior permanent magnet synchronous motor, IPMSM)电流和速度控制器。在该驱动系统中,空间矢量调制技术产生两电平逆变器开关控制信号。为了更加真实地模拟实际运行环境,仿真试验中考虑了逆变器的非线性特性,如死区时间、触发信号门槛值以及开关器件的电压降落。电机驱动系统中的PI控制器参数采用在线PSO算法进行实时调节,采样周期设为100 μs,硬件试验平台为DSPACE1104,且优化的目标函数值可以根据系统的动态和静态运行情况而改变。指令信号采用一阶阶跃信号。将PSO算法与传统的PI控制方法进行仿真和试验比较,结果表明采用PSO方法具有更好的鲁棒性和动态特性。
Abstract: A novel online particle swarm optimization method was proposed to design speed and current controller of vector controlled interior permanent magnet synchronous motor. In the proposed drive system, the space vector modulation technique was employed to generate the switching signals for a two-level voltage-source inverter. In order to simulate the system in the practical condition, the non-linearity of the inverter was also taken into account due to the dead-time, threshold and voltage drop of the switching devices. Speed and PI current controller gains were optimized with PSO online, sampling period was 100 μs, hardware test platform was DSPACE1104, and the fitness function was changed according to the system dynamic and steady states. The proposed optimization algorithm was compared with conventional PI control method in the condition of step speed change and stator resistance variation, which showed that the proposed online optimization method had better robustness and dynamic characteristics compared with conventional PI controller design