Fuzzy-PI Conroller Tuned With GWO, WOA And TLBO For 2 DOF Robot Trajectory Control

dc.contributor.author
dc.contributor.author Zennir Youcef
dc.contributor.author
dc.date.accessioned2024-05-08T13:57:22Z
dc.date.available2024-05-08T13:57:22Z
dc.date.issued2022-03-01
dc.description.abstractIn 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-Sugano 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 following a given trajectory
dc.identifier.issn2543-3792
dc.identifier.urihttp://dspace.univ-skikda.dz:4000/handle/123456789/1624
dc.language.isoen
dc.publisherALGERIAN JOURNAL OF SIGNALS AND SYSTEMS (AJSS).Vol. 7, Issue 1.pp01-06
dc.titleFuzzy-PI Conroller Tuned With GWO, WOA And TLBO For 2 DOF Robot Trajectory Control
dc.typeArticle
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