一类MIMO非线性系统的稳定自适应模糊控制

针对一类 MIMO不确定非线性系统 ,基于一种修改的李亚普诺夫函数并利用 I型模糊系统的逼近能力 ,提出一种分散自适应模糊控制器设计的新方案。该方案不但能够避免现有的一些自适应模糊 /神经网络控制器设计中对控制增益一阶导数上界的要求 ,而且能够避免控制器的奇异问题。通过理论分析 ,证明闭环控制系统是全局稳定的 ,跟踪误差收敛到零。仿真结果表明了该方法的有效性。

Stable Adaptive Fuzzy Control for a Class of MIMO Nonlinear Systems

A new scheme of decentralized adaptive fuzzy controller for a class of MIMO uncertain nonlinear systems is proposed in this paper. The design is based on a modified Lyapunov function and the approximation capability of the first type fuzzy systems. The approach is able to avoid the requirement of the upper bound of the first time derivative of the control gain, which is assumed to know a priori in some of the existing adaptive fuzzy/neural network control schemes. In addtion, it is also able to avoid the controller singularity problem. By theoretical analysis, the closed loop control system is proven to be globally stable in the sense that all signals involved are bounded, with tracking errors converging to zero. The simulation results are given to demonstrate the effectiveness of the approach.