Comparative analysis of noise robustness of type 2 fuzzy logic controllers

Comparative analysis of noise robustness of type 2 fuzzy logic controllers
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DOI:
10.14736/kyb-2018-1-0175
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发表时间:
2018-03
期刊:
影响因子:
0.5
通讯作者:
E. Ontiveros-Robles;P. Melin;O. Castillo
E. Ontiveros-Robles;P. Melin;O. Castillo
中科院分区:
计算机科学4区
文献类型:
--
作者:
E. Ontiveros-Robles;P. Melin;O. Castillo

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目前,模糊逻辑在控制应用中是一种公认的替代方案,这要归功于其固有的鲁棒性优势。然而,二类模糊逻辑方法允许管理模型中的不确定性。2型模糊逻辑最近在图像处理应用中显示出显著的改进,但是分析其对控制器性能的影响也很重要。本文比较了区间型-2和广义型-2模糊控制器的鲁棒性,从而得出在具体应用中哪种类型的控制器更好的准则。实验中考虑的对象是两个基准控制对象,我们报告了积分平方误差(ISE),积分绝对误差(IAE)和积分时间加权绝对误差(ITAE)性能指标,以及报告的另一个重要指标是执行时间。在实验结果的基础上,根据性能和执行时间要求,提出了模糊控制器的选择准则。
Nowadays Fuzzy logic in control applications is a well-recognized alternative, and this is thanks to its inherent advantages as its robustness. However, the Type-2 Fuzzy Logic approach, allows managing uncertainty in the model. Type-2 Fuzzy Logic has recently shown to provide significant improvement in image processing applications, however it is also important to analyze its impact in controller performance. This paper is presenting a comparison in the robustness of Interval Type-2 and Generalized Type-2 Fuzzy Logic Controllers, in order to generate criteria to decide which type of controller is better in specific applications. The plants considered in the experimentation are two benchmark control plants and we report the Integral Squared Error (ISE), Integral Absolute Error (IAE) and Integral Time-weighted Absolute Error (ITAE) performance metrics, and also another important metric reported is the execution time. Based on the experimental results, Fuzzy Logic Controller selection criteria are proposed according to the performance and execution time requirements.