DIRECT MODEL REFERENCE TAKAGI–SUGENO FUZZY CONTROL OF SISO NONLINEAR SYSTEMS DESIGN BY MEMBERSHIP FUNCTION

F. Hosseini, Meshkat Sadat Hosseini
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引用次数: 0

Abstract

What is discussed in this article is to find a way for membership functions optimally. In most scholars, these functions are constant and have a limited number. Therefore, in some cases, this limitation reduces control performance improvement. One of the best solutions is finding these functions in a differential form. This article used the Takagi-Sugeno function as a fuzzy detector to identify and control a nonlinear SISO system by direct adaptive reference model control. Using this method with Lyapunov for the stability of the control system makes output fuzzy linguistic variables optimally. Then simultaneously using these values, membership functions can be defined in differential form. Therefore, there is no other limitation in the variance and midpoint.
隶属函数在单索非线性系统设计中的直接模型参考takagi-sugeno模糊控制
本文讨论的是找到一种最优的隶属函数方法。在大多数学者中,这些函数是恒定的,并且数量有限。因此,在某些情况下,这种限制降低了控制性能的改进。最好的解决方法之一就是找到这些函数的微分形式。本文采用Takagi-Sugeno函数作为模糊检测器,通过直接自适应参考模型控制对非线性SISO系统进行辨识和控制。利用该方法与李雅普诺夫算法求解控制系统的稳定性,使输出的模糊语言变量达到最优。然后同时使用这些值,可以用微分形式定义隶属函数。因此,方差和中点没有其他限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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