一类不确定非线性系统的鲁棒自适应模糊控制

针对一类具有未知控制增益符号的不确定非线性系统。基于模糊系统的逼近能力，利用Nussbaum函数的性质，提出了一种自适应模糊控制器设计的新方案．该方案取消了函数控制增益符号已知这一条件，并通过引入最优逼近误差的自适应补偿项来消除建模误差和参数估计误差的影响．理论分析证明了闭环系统的有界性和跟踪误差收敛到零．仿真结果表明了该方法的有效性．

Robust adaptive fuzzy control for a class of unknown nonlinear systems

A design scheme of adaptive fuzzy controller for a class of uncertain nonlinear systems with unknown control gain sign is proposed in this paper. The design is based on the approximation capability of fuzzy systems and the property of Nussbaum function. The approach does not require a prior knowledge of the sign of the function control gain to be known. The adaptive compensation term of the optimal approximation error is adopted to minify the influence of modeling error and parameter estimation error. By theoretical analysis, the closed-loop control system is proved to be stable in the sense that all signals involved are bounded, with tracking error converging to zero. Simulation results demonstrate the effectiveness of the approach.