不确定非线性系统的自适应反推高阶终端滑模控制

针对一类非匹配不确定非线性系统,提出一种神经网络自适应反推高阶终端滑模控制方案.反推设计的前1步利用神经网络逼近未知非线性函数,结合动态面控制设计虚拟控制律,避免传统反推设计存在的计算复杂性问题,并抑制非匹配不确定性的影响;第步结合非奇异终端滑模设计高阶滑模控制律,去除控制抖振,使系统对于匹配和非匹配不确定性均具有鲁棒性.理论分析证明了闭环系统状态半全局一致终结有界,仿真结果表明了所提出方法的有效性.

Adaptive backstepping high-order terminal sliding mode control foruncertain nonlinear systems

A neural network adaptive backstepping high-order terminal sliding mode control scheme is proposed for a class of uncertain nonlinear systems with mismatched uncertainties.At the first 1 steps,neural networks are employed to approximate the unknown nonlinear functions and the dynamic surface control is combined with backstepping design technique to design the virtual controller,so that the explosion of complexity in traditional backstepping design is avoided and mismatched uncertainties are restrained perfectly.In the-th step,the high-order sliding mode control law is designed by combining with the non-singular terminal sliding mode to eliminate the chattering and make the system robust to both matched and mismatched uncertainties.By theoretical analysis,all the states in the closed loop systems are guaranteed to be semi-globally uniformly ultimately bounded.Finally,the simulation results show the effectiveness of the proposed method.