基于模糊神经网络算法的永磁同步电机位置控制

发布时间：2018-03-29 08:25

本文选题：永磁同步电机　切入点：位置伺服　出处：《东北大学》2014年硕士论文

【摘要】：永磁同步电机凭借其控制效果好、体积小、功率因数高、转矩电流比高、自身转动惯量低等优点在工业机器人、数控机床等高精度位置控制方面得到了广泛应用。本文首先对永磁同步电机位置控制系统的研究现状和发展前景做了简要分析；然后深入分析了永磁同步电机的数学模型,结合坐标变换对比分析了永磁同步电机在坐标变换前后的数学模型,并对永磁同步电机在两相旋转d-q坐标系下数学模型进行了解耦运算；采用了id=0的控制方法,使单位电流产生最大的电磁转矩；设计了三闭环调节的永磁同步电机位置控制系统。速度环和电流环采用PI控制,根据系统位置误差和误差变化率大小设计了模糊神经网络PID位置控制器。仿真实验,验证了模糊神经网络和PI相结合的控制策略的有效性和实用性,改善了系统的位置跟踪性能,提高了控制系统的快速性和稳定性。在常规模糊神经网络的基础上,进一步提出了补偿模糊神经网络位置控制器。实验结果验证了补偿模糊神经网络控制算法在永磁同步电机位置伺服系统中的优越性和可行性。
[Abstract]:Permanent magnet synchronous motor (PMSM) has the advantages of good control effect, small size, high power factor, high torque / current ratio, low moment of inertia and so on. High precision position control has been widely used in CNC machine tools. Firstly, the present situation and development prospect of PMSM position control system are briefly analyzed, and then the mathematical model of PMSM is deeply analyzed. Combined with coordinate transformation, the mathematical model of PMSM before and after coordinate transformation is analyzed, and the mathematical model of PMSM in two-phase rotating d-q coordinate system is decoupled, and the control method of id=0 is adopted. The position control system of PMSM with three closed-loop regulation is designed. The speed loop and current loop are controlled by Pi. The fuzzy neural network PID position controller is designed according to the position error and error rate of the system. The simulation results show the effectiveness and practicability of the control strategy combined with the fuzzy neural network and Pi. The position tracking performance of the system is improved, and the speed and stability of the control system are improved. Furthermore, a position controller based on compensatory fuzzy neural network is proposed, and the experimental results show the superiority and feasibility of the fuzzy neural network control algorithm in the position servo system of PMSM.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM341;TP183

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