一种等价于PI的二型模糊控制器设计算法

区间二型模糊集合将次隶属度做了简化,基于KM降阶算法的区间二型模糊控制器实现起来相对简单。虽然区间二型模糊控制器在一定程度上优于传统的一型模糊控制器或者PI控制器等,但区间二型模糊控制器并没有充分利用二型模糊集合的次隶属度信息。为解决这些问题,研究了普通二型模糊控制器的一般结构,提出了一种等价于PI的二型模糊控制器。该控制器基于普通二型模糊集合的α平面表现形式,在次隶属度函数的顶点处,将区间二型模糊集合简化为一型模糊集合。通过n阶有自平衡对象,无自平衡对象以及2个非线性对象的仿真结果表明,提出的二型模糊控制器能够得到较好的控制效果。

A Design Algorithm for Type 2 Fuzzy Controller Equivalent to PI

Interval type 2 fuzzy sets simplify the secondary membership function, thus the establishment of the interval type 2 fuzzy controller based on KM type reduction algorithm is relatively easy. Although the interval type 2 fuzzy controller is better than the tradition type 1 fuzzy controller or PI controller partly, the secondary membership function of type 2 fuzzy sets is not fully utilized in the interval type 2 fuzzy controller. The structure of the general type 2 fuzzy controller is discussed and a type 2 fuzzy controller equivalent to PI controller is proposed in this article. The controller is based on α plane presentation for general type 2 fuzzy sets, and at the vertex of the secondary membership function, the interval type 2 fuzzy sets is simplified to type 1 fuzzy sets. The simulation results of a n-order self-balanced plant, a non-self-balance plant and 2 nonlinear plants show that the proposed type 2 fuzzy controller can achieve better control effects.