一类非线性系统的模糊自适应跟踪控制

Fuzzy Adaptive Tracking Control for a Class of Nonlinear Systems

针对一类非线性系统,把模糊T-S模型和自适应模糊逻辑系统两种模糊逻辑方式结合起来,提出了一种基于观测器的跟踪控制方案。首先,应用模糊T-S模型对非线性系统建模,设计观测器用来观测系统状态;由线性矩阵不等式得到模糊模型的控制律。其次,构建了自适应模糊逻辑系统;应用基于权值、中心和宽度三个参数可调节的自适应模糊逻辑系统作为补偿器来补偿建模误差。文中证明了闭环系统满足期望的跟踪性能,实现了跟踪目的。两连杆机械臂的仿真结果表明该方案消除了建模误差对跟踪的影响。

Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an observer-based tracking control scheme for a class of nonlinear systems. Firstly, the fuzzy T-S model is used to approximate nonlinear systems, and an observer is designed to observe system states, and the fuzzy control law of the fuzzy model is derived by the linear matrix inequality. Secondly, adaptive fuzzy logic systems are constructed and modeling errors are eliminated by a compensator based on the adaptive fuzzy logic systems with three adjustable parameters: weights, centers and widths. It is proved that the closed-loop system satisfies the anticipant tracking performance, thus realizing the tracking target. Simulation results of a 2-link robotic manipulator demonstrate that the control scheme eliminates the effect of the modeling error for tracking.