PMSM中基于改进BFO算法的无传感器速度控制方案

A Sensorless Speed Control Scheme Based on Improved BFO Algorithm in PMSM

针对永磁同步电机(PMSM)矢量控制系统中传统PI速度控制器性能较差的问题,提出一种结合改进型细菌觅食优化(IBFO)算法和分数阶PI控制器的无传感器速度控制方案。首先,利用分数阶PI控制器代替传统PI控制器提高对时变、非线性控制系统的控制性能;然后,对传统BFO算法进行改进,通过融入粒子群优化算法中的信息共享机制,根据个体最优和全局最优来更新细菌位置;最后,以速度控制稳定性和超调量作为适应度函数,通过IBFO算法来优化分数阶PI控制器的参数,以获得最佳控制性能,并通过扩展卡尔曼滤波器(EKF)来估计电机实际转速。实验结果表明:与传统方法相比,提出的控制方法能快速且稳定地控制电机转速,具有较高的应用价值。

For the issues that the poor performance of the traditional PI speed controller in the PMSM vector control system,this paper proposed a sensorless speed control scheme combining the improved bacteria foraging optimization(IBFO)algorithm and the fractional PI controller.Firstly,it used fractional-order PI controller instead of the traditional PI controller,in order to improve the control performance for time-varying,non-linear control system.Then,it updated the bacterial location according to the optimal and global optimal of the information in the particle swarm optimization algorithm,so as to improvethe traditional BFO algorithm.Finally,it used the IBFO algorithm to optimize the parameters of the fractional PI controller with speed control stability and overshoot as the fitness function,in order to obtain the best control performance.In addition,the actual motor speed was estimated by extended Kalman filter(EKF).The experimental results show that compared with the traditional method,the proposed control method can control the speed of the motor quickly and steadily and therefore has high application value.