基于模糊树模型的自适应模糊滑模控制方法

Adaptive fuzzy sliding-mode control method based on fuzzy tree model

中文关键词  模糊树模型  自适应模糊控制  滑模控制

英文关键词  fuzzy tree model  sliding-mode control  adaptive fuzzy control

中文摘要

      本文针对单输入–单输出仿射非线性系统提出了一种基于模糊树模型的具有监督控制器的模糊滑模控制方法. 该方法用模糊树模型逼近非线性系统中的未知非线性函数, 得到初始的控制器, 然后在线调节模糊树模型中的线性参数, 改善控制器的性能, 实现对有界参考输入信号的跟踪控制. 模糊树辨识方法自适应划分输入空间, 大大减少模糊规则的数目, 在一定程度上可以缓解困扰模糊控制中的”规则爆炸”问题. 该方法通过监督控制器保证闭环系统所有信号有界. 通过理论分析, 证明了跟踪误差收敛到零. 用倒立摆进行仿真验证, 结果表明该方法用较少的模糊规则, 就能得到满意的控制效果, 有推广应用价值.

英文摘要

      Based on fuzzy tree model, an adaptive fuzzy sliding-mode control strategy with supervisory controller is proposed for a class of nonlinear systems. In this strategy, the unknown nonlinear functions are approximated by the fuzzy tree model to obtain the prototype controller; the linear parameters in the fuzzy tree model are adjusted online to improve the performance of the controller in realizing the tracking control to a bounded set point input. Because of the adaptive partition of the input space, the fuzzy tree identification methods greatly reduce the number of fuzzy rules. This avoids, in some extent, the problem of ”rule explosion” which often occurs in the fuzzy control for high dimension nonlinear systems. With the help of a supervisory controller, the resulting closed-loop-system is globally stable in the sense that all signals involved (states, controls, parameters, etc.) are uniformly bounded. By Lyapunov method, the tracking error is proved to be asymptotically converging to zero. The numerical simulation of controlling an inverted pendulum verifies the efficiency and advantage of the proposed method.