带有未建模动态的非线性系统的自适应动态面控制

Adaptive dynamic surface control of nonlinear systems with unmodeled dynamics

针对一类带有未建模动态的非线性纯反馈系统,利用神经网络逼近能力,提出一种自适应动态面控制方案.通过在传统后推设计中引入一阶滤波器,避免了对虚拟控制反复求导而导致的计算复杂性问题.利用Young’s不等式和积分型李亚普诺夫函数,有效地减少了可调参数的数目,无需虚拟控制增益系数导数的信息.理论分析表明了闭环控制系统是半全局一致终结有界的.

Based on the approximation capability of neural networks, adaptive dynamic surface control is presented for a class of nonlinear systems in pure feedback form with unmodeled dynamics. By introducing the first order filter, the explosion of complexity caused by the repeated differentiations of certain nonlinear functions such as virtual controls in traditional backstepping design is avoided. By using Young＇s inequality and integral-type Lyapunov function, the number of adjustable parameters are effectively reduced and the derivative of the virtual control coefficients is avoided to be known. Theoretical analysis shows that the closed-loop control system is semi-globally uniformly ultimately bounded.