自适应模糊小波滑模控制在交流伺服系统中的应用

针对某武器大功率交流伺服系统的位置跟踪问题，提出了一种基于自适应模糊小波神经网络快速终端滑模控制(AFWN-FTSMC)方法。为使控制器的设计不依赖于被控对象的精确数学模型，采用自适应模糊小波神经网络控制器(AFWNC)逼近滑模控制中的等效控制部分，解决了由于系统的不确定性及干扰的存在而不能准确确定等效控制的问题；同时利用自适应PI控制来降低系统的抖动，并采用Lyapunov方法证明了闭环系统的稳定性。仿真结果表明，该方法可以有效抑制抖振，提高系统的瞬态响应性能和控制精度，并且对结构参数不确定性具有很强的鲁棒性。

Application of Adaptive Fuzzy Wavelet Neural Sliding Mode Control in AC Servo System

An adaptive fuzzy wavelet neural network fast terminal sliding mode control (AFWN-FTSMC) approach is proposed to control the position of high power AC servo system in a certain weapon. An adaptive fuzzy wavelet neural network controller (AFWNC) is introduced to approach the equivalent control of sliding mode control, which solves the problem that the equivalent control can not be obtained accurately because of the uncertain parameter and external disturbances of the system. The controller can be designed without accurate mode. An adaptive proportional-integral (A-PI) law is used to eliminate system chattering. The stability of the closed loop system is guaranteed by using the Lyapunov method. Simulation results show that the proposed approach can not only improve the steady state performance and control accuracy, but also avoid the chattering problem effectively, and the structural parameter uncertainty has strong robustness.