PD型模糊学习控制及其在可重复轨迹跟踪问题中的应用

针对可重复轨迹跟踪问题,提出了一种PD型模糊学习算法.该算法集成两种控 制:作为基础的PD型模糊逻辑算法和改善系统性能的学习算法.模糊学习控制在模糊控制 基础上引入迭代学习算法,使得模糊PD控制器可以精确地跟踪可重复轨迹以及消除周期性 扰动.本文在能量函数和泛函分析的基础上,通过严格的推导表明PD型模糊学习算法可达 到:1)系统跟踪误差一致收敛到零;2)学习控制序列几乎处处收敛到理想的控制信号.

A PD Type Fuzzy Logic Learning Control Approach for Repeatable Tracking Control Tasks

In this paper, we consider repeatable tracking control tasks using a new control approach-PD type Fuzzy Logic Learning Control (FLLC). FLLC integrates two main control strategies: Fuzzy Logic Control as the basic control part and Learning Con- trol as the refinement part. The new FLLC is constructed by simply adding an iterative learning mechanism to a fuzzy PD controller. The incorporation of the,learning function into fuzzy PD controllers ensures exact tracking because it completely nullifies the effects of reference signal and periodic disturbances on the tracking error. Through rigorous proof based on energy function and functional analysis, we show that the proposed FLLC system achieves the following novel properties: (1) the tracking error sequence converges uniformly to zero; (2) learning control sequence converges to the desired control profile almost everywhere. Simulation is presented to show the validity of the proposed control method.