【作者】 王松；

【导师】 刘明光；

【作者基本信息】 北京交通大学 ， 电力系统及其自动化， 2011， 博士

【摘要】 摘要：交流永磁同步电机以其结构简单、运行可靠、体积小、损耗低、效率高等特点,在数控机床、电动汽车、机器人等方面获得了广泛应用。论文在对交流永磁同步电机的原理、数学模型和空间矢量脉宽调制(SVPWM)技术进行研究的基础上,对永磁同步电机的参数测试、辨识进行了大量的理论和实验研究,同时对永磁同步电机基于自抗扰和灰色理论的控制策略也进行了深入研究。仿真和实验结果验证了新的参数测试、辨识方法和自抗扰控制的有效性。论文对永磁同步电机的几个主要参数的测试方法进行了介绍。针对采用电压积分法测量交、直轴电感Lq,Ld中必须使用磁通计这一专用设备的要求,考虑到目前实验室和工作现场的实际情况,提出了一种替代解决方案,即：利用通用的电压采集装置(如：示波器)进行数据采集,然后采用数值积分法对采集到的离散电压信号进行积分,得到永磁电机的磁链参数,进而计算出永磁电机的电感参数。该方法具有简便、易于实现的特点。实验结果验证了该方法的有效性。针对永磁同步电机的绕组电阻Rs和交、直轴电感L。,Ld会随温度发生较大变化的问题,通过数学方法和仿真研究了这些参数随温度变化的辨识问题。论文在MATLAB中构造了一种参数能在线变化的永磁同步电机仿真模型,采用扩展卡尔曼(EKM)滤波和Elman神经网络,递推最小二乘方法进行了辨识。这两种辨识方法虽然也能达到较高的辨识精度,但由于存在计算中数据量大,难以实现实时辨识的缺点,提出了一种加窗最小二乘方法。该方法可根据实际要求确定所需的数据长度,计算量小,既保证了辨识精度又提高了实时性,还解决了递推最小二乘方法存在的数据饱和问题。这三种辨识方法的仿真结果比较表明：加窗最小二乘法具有最优的辨识效果。为进一步提高永磁同步电机工作的稳定性和控制性能,论文首先采用自抗扰控制技术对电源、转矩等扰动了有效抑制,仿真结果表明自抗扰的控制性能优于PID控制；论文在自抗扰控制的基础上,将最优控制、神经网络与自抗扰技术结合,提出了永磁同步电机自寻最优自抗扰控制和基于神经网络的自抗扰控制算法。永磁同步电机自寻最优自抗扰控制除了具有比自抗扰更高的控制性能以外,还具有控制能量最少的特点。为消除永磁同步电机伺服系统运行过程中存在的外部负载等扰动项的变化对调速性能的影响,论文将神经网络嵌入到自抗扰控制器中,利用神经网络能任意逼近非线性函数的能力去补偿对象的一部分变化,这样既可近似地使原系统参数变化范围变小,还能提高自抗扰控制的状态估计能力,从而减轻ESO的负担,有利于提高控制器的运算和响应速度。研究结果表明这两种方法可以提供比自抗扰更优的控制效果。为实现永磁同步伺服系统的参数在线辨识与控制,通过自行搭建的永磁同步电机模型,模拟温度从20℃-80℃时绕组电阻Rs和交、直轴电感Lq,Ld的变化情况,采用加窗最小二乘法实时辨识参数,转速环采用自抗扰控制。仿真结果显示：采用参数在线辨识的自抗扰控制系统性能比单纯采用PID的系统性能更优。为了利用“少数据”来实现永磁同步电机的控制,论文首次将灰色补偿PID和灰色预测PID控制算法同时应用到永磁同步电机伺服系统中,仿真结果表明：与PID控制相比,该控制策略对各种干扰具有更好的鲁棒性和适应性。自行研发了一套交流永磁同步电机伺服系统,实现了基于三闭环的SVPWM控制。伺服系统的空载和负载试验表明,与经典PID控制相比,自抗扰控制具有响应快、无超调、抗扰动能力强等特点。此外,针对IGBT驱动中存在现场参数变化问题,专门开发了一种可对IGBT开通和关断时间进行调节、具有驱动电源欠压保护功能的新型驱动电路,取得了良好的应用效果。更多还原

【Abstract】 ABSTRACT: Due to its uncomplicated structure, excellent control performance, small size, low loss and high efficiency, AC PMSM (Alternating Current Permanent Magnet Synchronous Motor) is widely used in the fields of Numerically-controlled machine tool, electric automobile, and robot, etc. Based on the research for its principle of work, its mathematical model and SVPWM (Space Vector Pulse Width Modulation), the author does a lot of theoretical and practical research for the tests as well as identification of PMSM’s parameters. Besides, control strategies of PMSM based on the theory of ADRC (active disturbance rejection control) and Gray Theory are also studied deeply. Simulation and experiment results demonstrate the effectiveness of new ways to test and identify parameters, as well as ADRC.A new method to test the several main parameters of PMSM is proposed in this paper. Since the magnet meter cannot be avoided in Voltage Integration method which is used to get Ld (direct-axis inductance) and Lq (quadrature-axis inductance) and considering the conditions of lab and worksite, this paper proposes an alternate method. Steps of this method are as follows. To begin with, data should be gathered by general devices of voltage collecting, such as oscilloscope. Then the discrete voltage signal can be integrated through Numerical-integration method to get PMSM’s flux linkage which can be used to compute its inductance. This method is simple and easy to implement. Experiment results have proved the effectiveness of this new method.Since Rs (wingding resistance), Ld and Lq will vary a lot with temperature, identification of these parameters are studied though mathematical analysis and simulation. The author has built a simulation model of PMSM in MATLAB whose parameters can vary online, and identified the parameters using EKF (Extended Kalman) filter & Elman neural network and RLS (Recursive Least Square) method. Despite that both of the two methods can guarantee high identification accuracy, they are unsuitable to identify online and have big compute loads. Based on the above disadvantages, WLS (Windowed Least Square) method is proposed. In this method, the length of the window can be adjusted according to practical conditions. Besides, it has a small computational burden. That is why it can guarantee the identification accuracy and excellent timeliness. And at the same time, the issue of data saturation of RLS can be avoided. Compared with simulation results of the other two methods, WLS’s results show that this method is the most effective.To improve the working stability and control performance of PMSM, ADRC is applied to reject disturbances from power supply and torque. Simulation results prove that the control performance of ADRC is better than PID control. Then, based on the ADRC theory, the author combines Optimal control, Neural networks and ADRC method together and proposes two algorithms named Self-optimizing ADRC method and ADRC based on neural networks, respectively. Compared with ADRC method, the Self-optimizing ADRC method has better control performance and least control energy. To eliminate the influence of varying disturbance like external load on the control performance of rotation speed, neural network is bedded in ADRC, which can approximately narrow the vary range of original system’s parameters, and at the same time improve ADRC’s ability of state estimation so that it is possible for ESO (Extended State Observer) to work with lighter load. What’s more, by doing this, controller’s computing and response speed will be improved. It is proved by study results that both of the methods can provide better control effect.In order to identify and control parameters of PMSM online, the author builds a control model of PMSM and simulates change process of Rs, Ld and Lq with temperature varying from 20℃to 80℃. Then the parameters are identified online using WLS method while ADRC is applied in speed loop. Simulation results demonstrate that the performance of ADRC system using online estimation strategy is better than that of the system using only PID method.In this paper, Gray Compensation PID algorithm and Gray Predict PID Control algorithm are applied in PMSM Servo System for the first time to control PMSM with less data, and results show that this control strategy has more satisfied robustness and adaptive capacity.A set of AC PMSM Servo System has been developed to realize the SVPWM control based on three closed loop. The load test and no-load test prove that ADRC has the advantages of fast response, no over modulation, and strong ability of rejecting disturbance, compared with classical PID control.In addition, since parameters of IGBT will change in work site, the author has developed a new kind of circuit which can modulate the turn-on and turn-off time of IGBT. Moreover, this driving circuit is also able to protect itself when power supply is under-voltage. And this kind of circuit is proved to be effective.更多还原