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针对一类过程结构和参数都存在很大不确定性或未知的非线性系统，利用模糊逻辑系统的逼近能力，提出了模型参考自适应模糊控制器设计的系统方法．基于μ－修正方案，建立了未知参数的自适应调节律．利用李雅普诺夫理论，证明了基于自适应模糊控制算法的闭环系统是全局稳定的，系统的跟踪误差在有限时间内可收敛到任意给定的零的一个邻域内．仿真结果显示了这一新方法的有效性．
For a class of nonlinear systems with large uncertainties or uncertainties in process structure and parameters, a system approach to model reference adaptive fuzzy controller design is proposed based on the approximation ability of fuzzy logic systems. Based on μ-correction scheme, an adaptive tuning law of unknown parameters is established. Using Lyapunov theory, it is proved that the closed-loop system based on adaptive fuzzy control algorithm is globally stable. The tracking error of the system can converge to a given neighborhood of zero within a finite time. Simulation results show the effectiveness of this new method.