基于改进广义预测控制算法的无刷直流电机控制仿真  

Simulation of Brushless DC Motor Control Based on an Improved Generalized Predictive Control Algorithm

作　　者：张帆 张向文[1] 

机构地区：[1]桂林电子科技大学电子工程与自动化学院,广西桂林541004

出　　处：《信息与控制》2017年第3期350-357,共8页Information and Control

基　　金：国家自然科学基金资助项目(51465011);广西区自然科学基金资助项目(2014GXNSFAA118377);桂林电子科技大学研究生教育创新计划资助项目(2016YJCX30);智能综合自动化广西高校重点实验室基金资助项目

摘　　要：针对无刷直流电机(BLDCM)负载运行时稳态跟踪误差大、电机性能受负载不确定性影响的缺点,提出了一种基于改进广义预测控制(GPC)算法的BLDCM调速方法.基于dSPACE公司汽车仿真模型(ASM)中的BLDCM模型设计了BLDCM的控制系统并进行仿真研究.仿真结果显示:当电机从静止跟踪到设定200r/min转速时,稳态精度达到0.5r/min;当电机受到幅值为1N·m的正弦波变化的负载扰动时,转速最大波动为1.5r/min,与传统比例—积分—微分(proportion-integral-derivative,PID)控制与滑模控制算法相比,所设计控制器使转速波动减小超过3.3%.因此,改进GPC算法控制器能够有效抑制负载扰动,提高系统转速跟踪精度.The brushless DC motor( BLDCM) has a large speed tracking error during the load operation process,and the motor's performance is affected by load uncertainty. To solve these problems,we propose an improved generalized predictive control( GPC) algorithm for BLDCM control. We design a BLDCM control system and simulate the system based on the BLDCM model from the dSPACE ASM software. Simulation results show that the steady-state accuracy is 0.5 r/min when the motor reaches the steady state of 200 r/min from stillness,and the greatest speed fluctuation is 1.5 r/min when motor is disturbed by a sinusoidal load with 1 Nm amplitude. Compared with the conventional proportion-integral-derivative( PID) control and sliding mode control,the designed controller decreases the speed fluctuation to lower than 3.3%. Thus,the improved GPC algorithm controller can restrain the load disturbance effectively and improve the system speed tracking precision.

关 键 词：广义预测控制d SPACE无刷直流电机模型调速负载扰动 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]