考虑输入饱和的异步电机随机命令滤波控制  

Adaptive Command Filtered Stochastic Nonlinear Control for IM with Input Saturation

作　　者：赵振华[1] 马玉梅[2] 于金鹏[1] 韩玉西 付程[1] 

机构地区：[1]青岛大学自动化与电气工程学院,山东青岛266071 [2]青岛大学计算机科学技术学院,山东青岛266071

出　　处：《青岛大学学报（工程技术版）》2017年第3期80-85,共6页Journal of Qingdao University(Engineering & Technology Edition)

基　　金：国家自然科学基金资助项目(61573204;61174131);山东省优秀青年基金重点项目(ZR2015JL022)

摘　　要：针对异步电机调速系统中存在的随机扰动问题,本文在传统反步法的基础上,利用神经网络逼近系统中的非线性函数,同时运用命令滤波技术,解决了传统反步法中存在的计算爆炸问题,实现了对考虑输入饱和的异步电机速度调节控制。为验证所设计控制器的有效性,利用Matlab进行仿真分析。仿真结果表明,本文设计的控制器能够有效抑制随机扰动,克服输入饱和的影响,可以很好地跟踪给定的期望信号,保证跟踪误差收敛在原点很小的邻域内。当t=5s时,负载转矩变化,系统仍能快速跟踪给定信号,实现了对异步电动机快速有效的控制。因此,该方法具有较高的理论研究意义和实用价值。This paper studies speed regulation control of the stochastic induction motor drive system with load disturbance based on backstepping. Neural networks are used to approximate unknown nonlinear functions and the command filtered backstepping is employed to construct controllers. The proposed control method can over-come the problems of ^parameter uncertainties^ and ^explosion of complexity^ inherent in the traditional back- stepping design. In order to verify the validity of the controller,Matlab is utilized to conduct the simulation. The simulation results show that the proposed adaptive neural network speed controllers can overcome the in-fluences of input saturation and make sure that the proposed approach track the given tracking signal well, and the tracking error converges to an arbitrarily small neighborhood around the origin. When t is equal to 5 sec-onds, the load torque changes, but it can still quickly track the given signal. Simulation results illustrate the effectiveness of the proposed approach. This study has some value in theoretical study and practical applications.

关 键 词：随机非线性系统 命令滤波 神经网络 异步电机 输入饱和 

分 类 号：TM343[电气工程—电机] TP273.2[自动化与计算机技术—检测技术与自动化装置]