基于粒子群优化的PMSM自抗扰前馈控制

Active disturbance Rejection Feedforward Control of PMSM Based on Particle Swarm Optimization

为提高自抗扰控制器的抗干扰能力,提出基于粒子群优化的PMSM自抗扰前馈控制策略。在传统自抗扰控制器基础上,设计新型级联观测器将观测出的部分扰动项前馈补偿到控制器中,采用粒子群优化算法对控制器中的重点可调参数进行迭代优化,引入扩展卡尔曼滤波器滤除电流测量中的干扰和噪声,提高系统控制性能。仿真结果表明:设计出的控制策略能有效提高系统的抗负载扰动能力,具有更平稳的稳态调速特性。

In order to improve the anti-interference ability of the active disturbance rejection controller,an active disturbance rejection feedforward control strategy of permanent magnet synchronous motor(PMSM)based on particle swarm optimization was proposed.Based on the traditional active disturbance rejection controller,a new cascade observer was designed to feed forward some observed disturbance terms to the controller.The particle swarm optimization algorithm was used to iteratively optimize the key adjustable parameters in the controller.The extended Kalman filter was introduced to filter out the interference and noise in the current measurement and improve the system control performance.The simulation results show that the designed control strategy can effectively improve the anti-load disturbance ability of the system and has more stable steady-state speed regulation characteristics.