不确定非线性系统的自适应反推终端滑模控制

针对一类具有未知非线性函数的严格反馈型不确定非线性系统,提出了一种自适应反推终端滑模控制方法。反推控制的前n-1步结合动态面控制技术设计虚拟控制律,第n步仅采用一个神经网络函数逼近器补偿系统所有未知非线性函数,得到了基于全局快速终端滑模控制的自适应神经网络控制器；通过引入一阶滤波器，不仅避免了传统反推控制存在的复杂计算,提高了系统的收敛速度,而且通过引入逼近误差和不确定干扰上界的自适应补偿项来消除建模误差和参数估计误差的影响,改善了稳态跟踪精度。理论分析证明闭环系统所有信号半全局一致终结有界，仿真结果验证了该方法的有效性。

Adaptive Aackstepping Terminal Sliding Mode Control for Uncertain Nonlinear Systems

An adaptive backstepping terminal sliding mode control scheme is proposed for a class of uncertain nonlinear systems in strict-feedback form with unknown nonlinearities. The dynamic surface control is combined with the first steps of backstepping method to design the virtual controller. In the -th step, only one neural network functions approximator is adopted to compensate all the unknown nonlinearities, and a adaptive neural network controller based on global fast terminal sliding mode design is obtained. The proposed controller design approach avoids the explosion of complexity in traditional backstepping design, and improves the convergence rate and steady-state tracking accuracy of the system by introducing approximation errors and adaptive compensation of uncertainty bounds to eliminate the errors of modeling and parameter estimation. By theoretical analysis, all the signals in the closed loop systems are guaranteed to be semi-globally uniformly ultimately bounded. Finally, the simulation results validate the effectiveness of the proposed method.