一类非线性系统的模糊滑模控制

针对一类非线性不确定系统，提出了一种模糊滑模控制器的设计方法。采用模糊神经网络设计系统控制器，基于梯度符号变化的局部学习率自适应BP算法，对模糊神经网络的隶属函数中心、宽度和网络权值进行调节，使滑模等效控制的模糊系统后件参数是自适应的；在系统存在外部干扰并有界时，利用李亚普诺夫方法证明了系统控制的稳定性。通过Matlab仿真分析，表明了所设计的模糊滑模控制器不但具有鲁棒性，而且具有良好的跟踪性能。

Fuzzy Sliding-mode Control for a Class of Nonlinear Systems

The method of fuzzy sliding-mode controller is proposed for a class of uncertain nonlinear systems.The plant is obtained by the infinite approach of fuzzy neural networks.The amelioration BP algorithm with adaptive partial learning rate based on changeable gradient mark is introduced to train the weight,the center and the width of membership,so that the fuzzy system parameter of the sliding-mode equivalent control is adaptive.When the external disturbance has a boundary,the system stability is proved by using Lyapunov method.The simulation with Matlab Shows that the robust control is realized and the sliding-mode controller can achieve better tracking performance.