考虑铁损的永磁同步电动机神经网络命令滤波控制

发布时间：2018-03-21 08:05

本文选题：铁芯损耗　切入点：永磁同步电动机　出处：《青岛大学》2017年硕士论文　论文类型：学位论文

【摘要】：在交流传动系统中,永磁同步电动机因其能量转换效率高、调速范围宽、转矩惯性比大、动静态特性好以及使用寿命长等特点已经广泛的应用于农业、工业等领域。然而,永磁同步电动机是一个耦合度强、扰动量大和参数时变的高度非线性系统。同时普遍存在于电动机系统中的铁芯耗损问题会影响到电动机运行性能,特别地,从能源意义、环保意义以及产业意义来讲,也将会影响某些电动机驱动对象诸如电动汽车等的整体性能。而且传统控制策略大多研究的是没有考虑铁芯损耗的永磁同步电动机的模型。因此,优化考虑铁损的永磁同步电动机驱动系统的控制策略,已经成为国内外控制领域研究的热点和难点。本文主要设计新型的考虑铁损的永磁同步电动机驱动系统的控制策略。针对永磁同步电动机经典控制策略中的不足之处,本文基于命令滤波技术和反步控制方法,研究了新型的自适应神经网络位置跟踪和速度调节控制策略。论文的主要研究成果如下:第一,研究了基于命令滤波技术和反步控制方法的非线性系统的自适应神经网络跟踪控制策略。利用神经网络逼近特性来处理系统中未知的非线性函数项,引入命令滤波技术,使用命令滤波器处理虚拟控制函数以消除“计算爆炸”现象,采用反步控制方法来构造自适应神经网络控制器,并使用Lyapunov方法对系统进行了稳定性分析。第二,基于命令滤波技术和神经网络逼近特性,并采用自适应反步控制方法构造了考虑铁损的永磁同步电动机位置跟踪控制器。利用神经网络逼近特性来处理系统中未知的非线性函数项,通过命令滤波器处理虚拟控制函数以消除“计算爆炸”现象,采用反步控制方法构造闭环系统的位置跟踪控制器,有效的避免了电动机系统参数时变和负载扰动等未知因素的影响,应用Lyapunov方法证明了系统的稳定性。与基于动态面技术控制方法进行对比仿真实验,验证了应用命令滤波技术所构造的位置跟踪控制器能够更好地跟踪设定信号以达到期望的控制目标。第三,研究了基于命令滤波误差补偿机制的考虑铁损的永磁同步电动机电机的速度调节控制器。利用神经网络逼近特性对系统中的非线性函数进行有效逼近,通过命令滤波器消除“计算爆炸”现象,引入滤波误差补偿信号减小了命令滤波器产生的滤波误差。基于Matlab/Simulink仿真实验环境,保证闭环系统信号完全有界,证明了所构造控制器能够确保系统实现良好的控制效果。
[Abstract]:In AC drive system, permanent magnet synchronous motor because of its high energy conversion efficiency, wide range of speed, torque inertia ratio, dynamic characteristics of the application of good static characteristic and long service life has been widely in agriculture, industry and other fields. However, the permanent magnet synchronous motor is a strong coupling, nonlinear perturbation large and time-varying parameters. The core loss also exists in the motor system will affect the operation performance of the motor, in particular, from the energy industry and environmental protection significance, meaning sense, will also affect the overall performance of the driving motor of certain objects such as electric cars. But most of the traditional control strategy is not permanent magnet synchronous motor considering iron loss model. Therefore, the optimization of permanent magnet synchronous motor drive system control strategy considering iron loss, has become the domestic and foreign control. The hot and difficult area of research. This paper mainly consider the design of control strategy of permanent magnet synchronous motor drive system of the new type of loss. For permanent magnet synchronous motor control strategies in the classical deficiencies, the command filter and backstepping control method based on adaptive neural network model of position and speed control strategy. The main research results of this paper are as follows: first, the study of adaptive neural network command filtering techniques and control methods of backstepping nonlinear system control strategy based on nonlinear function. By using the neural network approximation properties to process system unknown, introducing command filter technology, using the command filter virtual control function to eliminate the "computation explosion" the phenomenon, using backstepping control method to construct the adaptive neural network controller, and the system using Lyapunov method For the stability analysis. Second, command filter and neural network approximation based on the characteristic, and the adaptive backstepping control method to construct the position of permanent magnet synchronous motor considering iron loss tracking controller. Nonlinear function approximation using neural network properties to process system unknown, through the command filter processing the virtual control function to eliminate the "computation explosion" phenomenon, using backstepping control method to construct the closed-loop position tracking controller, effectively avoid the influence of motor parameter variation and load disturbance and other unknown factors, the application of Lyapunov method to prove the stability of the system. And the dynamic control method which is based on the comparative experiments show that the structure of the application command filter technology position tracking control is better able to track the signal to achieve the desired controller. Third, on the base Considering the motor of permanent magnet synchronous motor speed regulating controller loss to the command filter error compensation mechanism. By using the neural network approximation properties of nonlinear functions in the system for effective approximation, computational explosion phenomenon ", through the command filter to eliminate the filter error compensation signal reduces the filtering error command filter produces Matlab/Simulink simulation environment. Based on the closed-loop system signal completely bounded, prove that the constructed controller can ensure the system to achieve good control effect.

【学位授予单位】：青岛大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP273;TM341

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