基于布谷鸟搜索算法优化的BLDCM角度控制

当前,经典比例积分微分(PID)控制在无刷直流电机(BLDCM)控制领域仍然占据十分重要的地位。为了解决传统PID控制器参数优化费时、最佳控制性能难以保证的问题,提出使用布谷鸟搜索(CS)算法优化PID控制器(CS-PID)构成电机的角度位置控制。其次,选用时间乘绝对误差积分(ITAE)函数作为CS算法的适应性函数,为PID控制器参数优化的合理性提供参考。最后,以粒子群算法优化PID(PSO-PID)控制器为基准,利用MATLAB仿真软件在恒定阶跃函数下分别对CS-PID控制器和PSO-PID控制器进行了实验测试。仿真试验结果表明:CS-PID控制器具有较好的控制性能指标;相对于PSO-PID控制器,CS-PID控制器优化算法具有优越性和有效性。

BLDCM Angle Control Based on Cuckoo Search Algorithm Optimization

At present,the classical proportion integration differentiation(PID)control still occupies a very important position in the field of brushless DC motor(BLDCM)control.In order to solve the problem of time-consuming optimization of traditional PID controller parameters and difficulty in guaranteeing the best control performance,it is proposed to use the cuckoo search(CS)algorithm to optimize the PID controller(CS-PID)to form the angular position control of the motor.Secondly,integral of time multiplied by absolute error(ITAE)function of the absolute error is selected as the adaptive function of the CS algorithm to provide a reference for the rationality of the PID controller parameter optimization.Finally,using the particle swarm optimization PID(PSO-PID)controller as a benchmark,the CS-PID controller and PSO-PID controller were tested experimentally using MATLAB simulation software under a constant step function.The simulation test results show that the CS-PID controller has better control performance indicators.Compared with the PSO-PID controller,the CS-PID controller optimization algorithm has superiority and effectiveness.