无轴承永磁同步电机非线性控制系统的研究

发布时间：2018-04-21 18:30

本文选题：无轴承永磁同步电机 + 转子初始位置辨识　；参考：《华南理工大学》2014年博士论文

【摘要】：无轴承永磁同步电机（Bearingless Permanent Magnet Synchronous Motor(BPMSM)）是一种新型的集旋转与转子自悬浮功能于一体的电机。具有无摩擦、无磨损、不需润滑和密封、精度高、维护小，成本低等优点，且不需激磁电流，因此在化学泵、蜗轮分子泵、血泵、高速磨粉机、压缩机及高速飞轮等设备广泛应用。与普通永磁同步电机相比，BPMSM稳定运行时转子处于自悬浮状态，外界扰动、参数摄动等因素使转子位置、速度及径向位移更容易产生振动和突变。本文围绕BPMSM悬浮力产生机理对BPMSM数学模型、非线性解耦控制，无位置传感运行进行了深入的理论分析与试验研究。以面贴式四极转矩绕组和二极悬浮绕组BPMSM为例，从麦克斯韦张量法出发，对悬浮力产生机理进行深入分析，考虑永磁体、转矩绕组、悬浮绕组和转子偏心等因素，分析和建立了悬浮力数学模型及电磁转矩数学模型，同时从转子动力学出发，建立转子运动方程及系统运动方程。研究了基于转子磁场定向控制的非线性解耦，控制系统采用PID控制悬浮绕组的径向悬浮力，采用PI控制转速，但在负载扰动的时候动态性能差，因此首次将分数阶PIλ控制器应用到BPMSM控制中，分数阶控制器具有很多整数阶系统无法实现的优越性，仿真实验表明采用分数阶PIλ控制器的BPMSM控制系统比采用整数阶PI控制BPMSM控制系统具有更快的响应速度、更好的抗干扰性能，鲁棒性好。为了解决系统在系统参数和扰动变化产生的抖振问题，将智能控制和分数阶结合起来，，设计了基于神经网络的分数阶滑模控制器，控制悬浮绕组的径向悬浮力，以减少抖振的发生。仿真和实验结果说明了神经网络分数阶滑模控制系统不但能削减抖震，而且能达到较高的综合控制性能。研究结果为智能分数阶控制器在BPMSM悬浮控制系统中的应用提供了理论依据，为进一步开展BPMSM高速运行稳定悬浮奠定基础。针对BPMSM无位置传感器运行的要求，提出了基于滑模观测器的BPMSM无传感器运行控制研究并通过实验验证BPMSM无位置传感器运行。最后归纳了本文的研究成果和创新工作，并对进一步的研究提出了建议。
[Abstract]:Bearingless Permanent Magnet Synchronous Motor (BPMS MMC) is a new type of motor with the function of rotation and rotor self-suspension. With no friction, no wear, no lubrication and sealing, high accuracy, small maintenance, low cost, and no magnetic current, so in chemical pump, worm wheel molecular pump, blood pump, high speed grinding machine, Compressor and high-speed flywheel and other equipment widely used. Compared with ordinary permanent magnet synchronous motor (PMSM), the rotor is in self-suspension state when BPMSM is running stably, and the external disturbance and parameter perturbation make the rotor position, speed and radial displacement more prone to vibration and sudden change. In this paper, the mathematical model of BPMSM, nonlinear decoupling control and sensorless operation of BPMSM are studied theoretically and experimentally around the mechanism of BPMSM suspension force generation. Taking the surface mount quadrupole torque winding and the two-pole suspension winding BPMSM as examples, starting from Maxwell Zhang Liang's method, the mechanism of levitation force is deeply analyzed, and the factors such as permanent magnet, torque winding, suspension winding and rotor eccentricity are considered. The suspension force mathematical model and the electromagnetic torque mathematical model are analyzed and established. At the same time, the rotor motion equation and the system motion equation are established according to the rotor dynamics. The nonlinear decoupling based on rotor flux oriented control is studied. The control system uses PID to control the radial levitation force of the suspension winding and Pi to control the rotational speed, but the dynamic performance is poor when the load is disturbed. Therefore, the fractional Pi 位 controller is applied to BPMSM control for the first time. The fractional order controller has many advantages that can not be realized by integer order system. The simulation results show that the BPMSM control system with fractional Pi 位 controller has faster response speed, better anti-jamming performance and better robustness than the integer Pi control BPMSM control system. In order to solve the buffeting problem caused by the variation of system parameters and disturbances, a fractional sliding mode controller based on neural network is designed to control the radial levitation force of suspension windings by combining intelligent control with fractional order. To reduce the occurrence of buffeting. Simulation and experimental results show that the neural network fractional sliding mode control system can not only reduce shaking, but also achieve a higher comprehensive control performance. The results provide a theoretical basis for the application of intelligent fractional-order controller in BPMSM suspension control system, and lay a foundation for the further development of high-speed and stable suspension of BPMSM. In order to meet the requirements of BPMSM sensorless operation, a sliding mode observer based BPMSM sensorless operation control is proposed. The experimental results show that the BPMSM sensorless operation is sensorless. Finally, this paper summarizes the research results and innovative work, and puts forward suggestions for further research.
【学位授予单位】：华南理工大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TM341

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