永磁同步电机的自抗扰控制器参数自整定

Parameter Self-tuning of ADRC for PMSM

摘要:

当永磁同步电机的工作环境和工作任务发生改变时,被控对象的模型会出现较大的变化。由于每次模型改变都要对控制器的参数进行调整,为了简单、快速的对线性自抗扰控制器的参数进行整定,设计了一种基于改进粒子群的算法的参数自整定方法。该算法引入了自适应权重因子从而兼顾了粒子的局部搜索能力和全局搜索能力。为了避免粒子陷入局部最优解,采用了对粒子群进行柯西变异的方法使粒子跳出局部最优从而找到全局最优解。仿真实验表明,采用改进粒子群算法整定的线性自抗扰控制器具有更高的跟踪精度和更强的抗干扰能力,且比标准粒子群算法具有更快的收敛速度和更高的收敛精度。

Abstract:

When the working environment and task of PMSM change, the model of the controlled object will change greatly. Because every time the model changes, the parameters of the controller must be adjusted. In order to adjust the parameters of the linear ADRC simply and quickly, a parameter self-tuning method based on the improved particle swarm optimization algorithm is designed. The adaptive weight factor is introduced in the algorithm, which takes into account the local search ability and global search ability of particles. In order to avoid the particle falling into the local optimal solution, the Cauchy mutation method is used to make the particle jump out of the local optimal solution and find the global optimal solution. Simulation results show that the improved PSO algorithm can achieve better control effect.