二类模糊控制器优化设计的元启发式优化算法

H. Patel
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引用次数: 2

摘要

利用勒维飞行来创建新的候选解决方案是CS最强大的元素之一。使用这种方法,通过进行许多小的修改和一些大的跳跃来修改候选解决方案。因此,CS将能够显著增加勘探和开发之间的联系,同时也提高其搜索能力。本研究将布谷鸟搜索优化(CSO)算法应用于区间2型模糊逻辑控制器(IT2FLC),确定区间2型模糊逻辑系统(it2fls)的隶属函数(MFs)的最优参数。该研究考虑了两种形式的MFs:三角形和梯形。当在每个控制问题的执行过程中施加扰动时,CSO算法的性能和效率显著提高。利用水箱控制器和倒立摆控制器两个基准控制问题对该方法进行了测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Metaheuristic Optimization Algorithm for Optimal Design of Type-2 Fuzzy Controller
The utilization of Le`vy flight to create new candidate solutions is one of the most powerful elements of CS. Candidate solutions are modified using this method by making a lot of minor modifications and a few big jumps. As a result, CS will be able to significantly increase the link between exploration and exploitation while also improving its search capabilities. The cuckoo search optimization (CSO) algorithm is applied to interval type-2 fuzzy logic controller (IT2FLC) in this research to determine the optimal parameters of membership functions (MFs) of interval type-2 fuzzy logic systems (IT2FLSs). The study takes into account two forms of MFs: triangular and trapezoidal. When perturbations are applied during the execution of each control issue, the CSO algorithm's performance and efficiency improve significantly. The proposed approach is tested using two benchmark control problems: water tank controller and inverted pendulum controller.
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