含非线性输入的非线性系统自适应模糊控制

Adaptive fuzzy control for a class of nonlinear systems with input nonlinearity

讨论一类含非线性输入的非线性系统的自适应模糊控制问题。首先运用隐函数存在定理证明系统的理想控制器的存在性,利用I型模糊逻辑系统对该理想控制器进行在线逼近,提出了一种具有监督器的自适应模糊滑模控制器设计的新方案。该方案通过直接自适应模糊控制器与监督控制器的适当切换,保证了闭环系统的稳定性,由此确定出建模的有界区域,而且通过引入最优逼近误差的自适应补偿项,保证跟踪误差收敛到零。仿真结果表明了该方法的有效性。

The problem of adaptive fuzzy control for a class of nonlinear systems with input nonlinearity is studied. Firstly the existence of the ideal control is proved by using the implicit theorem. The first type fuzzy system is employed to approximate the ideal control. A novel scheme of adaptive fuzzy control with a supervisory controller is proposed. By the proper switching between the direct adaptive fuzzy controller and the supervisory controller, the resulting closed-loop system is globally stable in the sense that all signals involved are uniformly bounded. Furthermore, the adaptive compensation term of the optimal approximation error is adopted to reduce the effects of modeling errors. By Lyapunov method, the tracking error is asymptotically converged to zero. Simulation results illustrate the effectiveness of the proposed approach.