基于快速终端滑模的永磁同步电动机位置跟踪控制研究  

Research on Position Tracking Control Method of PMSM Based on RBF Neural Network Fast Terminal Sliding

作　　者：潘云忠 刘琳霞[1] 

机构地区：[1]苏州健雄职业技术学院,太仓215411

出　　处：《微特电机》2016年第1期39-42,47,共5页Small & Special Electrical Machines

摘　　要：针对永磁同步电动机伺服系统在位置控制中受到外部扰动、电机参数时变、机械传动间隙影响等问题,提出了一种基于径向基神经网络快速终端滑模的电机位置跟控制方法。在分析永磁同步电动机数学模型的基础上,基于快速终端滑模控制理论,设计了一种快速终端滑模的永磁同步电动机速度跟踪控制算法;并对电机参数的时变性,提出了一种新型的RBF神经网络快速终端滑模控制的位置控制算法;利用李雅普诺夫函数证明了系统的稳定性。仿真实验结果表明:与传统的PI控制、单独的快速终端滑模控制相比,该算法能够有效提高永磁同步电动机的响应速度、鲁棒性以及电机位置跟踪精度,从而提高了永磁同步电动机的控制性能。Aiming at the problem of servo system of permanent magnet synchronous motor, such as subject to external disturbances in position control, the motor parameters variation and effect of mechanic transmission clearance, a motor posi- tion control method based on RBF neural network fast terminal sliding mode was presented. On the basis of the analysis of permanent magnet synchronous motor mathematical model, based on the fast terminal sliding mode control theory, a fast terminal sliding mode control of permanent magnet synchronous motor speed tracking algorithm was designed ; and for time- varying of the parameters of the motor, a new RBF neural network fast terminal sliding mode control of position control algo- rithm was proposed. Lyapunov function was used to prove the stability of the system. The simulation results show that com- pared with traditional PI control and separate the fast terminal sliding mode control, the proposed algorithm can effectively improve the permanent magnet synchronous motor response, robustness and the motor position tracking precision, which can improve the control performance of permanent magnet synchronous motor.

关 键 词：永磁同步电动机 位置控制 滑模控制 径向基神经网络 

分 类 号：TM341[电气工程—电机] TM351