非线性系统模糊间接自适应控制的后推设计

采用模糊神经网络作为非线性逼近器，针对一类一阶非线性多入多出系统，提出了一种具有扰动抑制的鲁棒自适应控制方法，给出了高阶多入多出系统具有扰动抑制的自适应后推(backstepping)设计方法。在鲁棒项合理简化的情况下，给出了系统Lyapunov意义下的稳定性证明，简略分析了各设计参数的物理意义及其对系统性能的影响。理论分析和仿真实验均显示，本方法可以保证系统的全局渐近稳定性，且若选取恰当的设计参数可保证系统对输入信号的跟踪达到任意精度；由于鲁棒项的引入可使系统的设计更具灵活性。

Backstepping design of robust indirect fuzzy controller for nonlinear systems

The adaptive control of strict-feed back nonlinear systems using fuzzy indirect method is focused on in this paper. Firstly, an adaptive controller, which includes a continued robust term for disturbance rejection, is presented for a kind of first-order multi-input/multi-output (MIMO) systems, with fuzzy networks as approximators of nonlinear functions. Then, a scheme of robust backstepping design is given for corresponding MIMO ones. The stability is proved using Lyapunov theories, during which the robust terms are substituted by approximate functions. Finally, the physical senses and influences on the system performance are analyzed simply. The result suggests that the asymptotic stability of the system can be gu aranteed, and the tracking errors can be arbitrary small when the designing parameters are given suitably. System design is flexible because of the robust terms introducing.