基于GWO、WOA和TLBO的模糊pi控制器用于二自由度机器人的轨迹控制

Mourad Achouri, Y. Zennir, C. Tolba
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引用次数: 5

摘要

本研究采用灰狼优化算法(GWO)、鲸鱼优化算法(WOA)和基于教学的优化算法(TLBO)三种元启发式算法对两自由度机械臂机器人进行Fuzzy-PI调节控制。在平均误差绝对值(MAE)的代价函数下,对takagi-soguno型模糊系统的尺度因子(隶属函数的宽度)和PI参数进行了优化。为了研究所提控制器的鲁棒性,我们考虑了摩擦力。仿真结果证明了该控制器对给定轨迹的跟踪效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy-PI Conroller Tuned With GWO, WOA And TLBO For 2 DOF Robot Trajectory Control
In this study, a manipulator robot with two degrees of freedom was controlled by Fuzzy-PI adjust by three meta-heuristic algorithms (Grey wolf optimizer (GWO), Whale Optimization Algorithm (WOA) and Teaching–learning-based optimization (TLBO)). The scale factors of the fuzzy system of the takagi-soguno type (the width of the membership functions) and the parameters of PI were optimized by those three algorithms under the cost function of the absolute magnitude of the mean error (MAE). In order to investigate the robustness of the proposed controller we considered the friction forces. The results of the simulation prove the controller's effectiveness to follow a given trajectory.
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