基于分数阶PI~λ的交流伺服系统控制策略研究

发布时间：2018-08-20 20:11

【摘要】：交流伺服系统因控制精度高,性能好在工业生产中得到了普遍的应用,然而随着工业自动化的快速发展,人们对交流伺服系统控制性能的要求也在不断提高。PID控制器依旧是交流伺服系统普遍采用的控制方式,虽然其结构简单,易于实现,但在系统参数变化以及外部干扰存在时其鲁棒性不够理想。近年来,由于分数阶微积分理论的快速发展,分数阶控制器得到了广泛的研究,它表现出了比传统PID控制器更为优越的性能。本文以提高交流伺服系统控制性能为目标,研究分数阶控制器在交流伺服系统中的应用。首先,本文介绍了分数阶控制理论和永磁同步电机的数学模型,探讨了永磁同步电机交流伺服系统的矢量控制原理,分析了伺服系统的电流环PI控制器、速度环PI控制器和分数阶PIλ控制器的设计方法,研究了空间矢量脉宽调制技术,并在此基础上搭建了永磁同步电机交流伺服系统的仿真模型。通过对分别使用整数阶PI控制器和分数阶PIλ控制器的伺服系统进行仿真实验,得到的结果表明分数阶PIλ控制器可以有效地提高伺服系统的抗干扰能力。其次,针对伺服系统的分数阶PIλ控制器参数较多,整定困难,设计了一种基于差分进化算法的控制器参数优化方法。由于标准的差分进化算法存在着不足,通过改变初始进化群体的选取方式,为变异因子和交叉概率设计动态的调节策略来改进算法,并利用测试函数验证了算法改进的正确性。之后,将改进的算法运用于交流伺服系统分数阶PIλ控制器的参数寻优上,仿真实验表明,改进的算法能够快速的搜索到伺服系统理想的控制器参数值,实现控制器参数的离线整定。最后,为交流伺服系统设计了一种基于RBF神经网络的分数阶PIλ控制器,该控制器用RBF神经网络辨识被控对象的Jacobain信息来自适应的整定分数阶PIλ控制器的参数,既利用模型的信息避免了人工整定的不确定性,又兼备了分数阶PIλ控制器的灵活性和鲁棒性。仿真实验的结果表明本文提出的RBF神经网络分数阶PIλ控制器能够很好的改善伺服系统的控制性能。
[Abstract]:Ac servo system has been widely used in industrial production because of its high control precision and good performance. However, with the rapid development of industrial automation, The requirements of AC servo system control performance are also continuously improved. Pid controller is still widely used in AC servo system, although its structure is simple and easy to realize. However, the robustness of the system is not ideal when the system parameters change and the external disturbances exist. In recent years, due to the rapid development of fractional calculus theory, fractional order controller has been widely studied, and it shows better performance than traditional PID controller. In order to improve the control performance of AC servo system, the application of fractional controller in AC servo system is studied in this paper. Firstly, the fractional order control theory and the mathematical model of PMSM are introduced, the vector control principle of PMSM AC servo system is discussed, and the current loop Pi controller of PMSM is analyzed. The speed loop Pi controller and fractional order Pi 位 controller are designed, and the space vector pulse width modulation (SVPWM) technology is studied. Based on this, the simulation model of PMSM AC servo system is built. The simulation results of the servo system using integer Pi controller and fractional Pi 位 controller show that the fractional Pi 位 controller can effectively improve the anti-interference ability of the servo system. Secondly, a parameter optimization method based on differential evolution algorithm is designed for the fractional Pi 位 controller of servo system, which has many parameters and is difficult to adjust. Due to the shortcomings of the standard differential evolution algorithm, the algorithm is improved by changing the selection method of the initial evolutionary population and designing dynamic adjustment strategies for the mutation factor and the crossover probability, and the correctness of the improved algorithm is verified by using the test function. Then, the improved algorithm is applied to the parameter optimization of the fractional Pi 位 controller of AC servo system. The simulation results show that the improved algorithm can quickly search the ideal controller parameters of the servo system. The off-line tuning of controller parameters is realized. Finally, a fractional-order Pi 位 controller based on RBF neural network is designed for AC servo system. The controller uses RBF neural network to identify the parameters of the controlled object's Jacobain information from the adaptive tuning fractional Pi 位 controller. Not only the uncertainty of manual tuning is avoided by using the information of the model, but also the flexibility and robustness of fractional Pi 位 controller are presented. The simulation results show that the RBF neural network fractional Pi 位 controller can improve the control performance of servo system.
【学位授予单位】：江苏科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM921.541

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