非线性增益递归滑模动态面自适应NN控制

Recursive Sliding-mode Dynamic Surface Adaptive NN Control with Nonlinear Gains

针对一类严反馈非线性不确定系统的跟踪控制问题,提出一种非线性增益递归滑模动态面(Dynamic surface control,DSC)自适应控制方法.通过设计一个新的非线性增益函数,并构造递归滑模动态面的控制策略和新的Lyapunov函数,同时利用神经网络在线逼近系统不确定项,该方法有效解决了具有输入饱和约束条件下系统控制精度与动态品质间的矛盾,增强了控制器对其自身参数摄动的非脆弱性.理论证明了闭环系统所有状态是半全局一致最终有界的,且跟踪误差可收敛至任意小.

A novel recursive sliding-mode dynamic surface adaptive control with nonlinear gains is proposed for the tracking problem of nonlinear systems in strict-feedback form. By designing a new function with nonlinear gains, contriving the strategy of recursive sliding-mode dynamic surface control （DSC） and novel Lyapunov function, and at the same time, using neural networks to approximate system uncertainty online, the new approach is able to effectively solve the contradiction of possess high control accuracy and good transient performance at the same time in the presence of input saturation and the designed controller is non-fragile to the perturbation of its own parameters. Stability analysis guarantees the semi-globally uniformly ultimate boundedness of the solution of the closed-loop system, and that ultimate tracking error bound in regulation can be made arbitrarily small.