{"title":"模糊规则仿真网络的等效分段导数自适应控制及灾难性遗忘学习的缓解","authors":"Chidentree Treesatayapun","doi":"10.1109/TSMC.2024.3490372","DOIUrl":null,"url":null,"abstract":"This article presents a novel adaptive control approach for a class of unknown discrete-time systems using piecewise derivatives derived from experimentally obtained input-output characteristics of the controlled plant. The control law is formulated using a multi-input fuzzy rules emulated network (MiFREN). The learning law is developed to address the issue of catastrophic forgetting, in alignment with the proposed information matrix. Closed-loop analysis demonstrates convergence of the tracking error and weight parameters under feasible conditions. Validation through experiments with a DC-motor torque control system, alongside comparative controllers, demonstrates the superior tracking performance of the proposed method and its effective mitigation of forgetting during tracking tasks.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 1","pages":"758-767"},"PeriodicalIF":8.6000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Equivalent Piecewise Derivative Adaptive Control With Fuzzy Rules Emulated Network and Mitigation of Catastrophic Forgetting Learning\",\"authors\":\"Chidentree Treesatayapun\",\"doi\":\"10.1109/TSMC.2024.3490372\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a novel adaptive control approach for a class of unknown discrete-time systems using piecewise derivatives derived from experimentally obtained input-output characteristics of the controlled plant. The control law is formulated using a multi-input fuzzy rules emulated network (MiFREN). The learning law is developed to address the issue of catastrophic forgetting, in alignment with the proposed information matrix. Closed-loop analysis demonstrates convergence of the tracking error and weight parameters under feasible conditions. Validation through experiments with a DC-motor torque control system, alongside comparative controllers, demonstrates the superior tracking performance of the proposed method and its effective mitigation of forgetting during tracking tasks.\",\"PeriodicalId\":48915,\"journal\":{\"name\":\"IEEE Transactions on Systems Man Cybernetics-Systems\",\"volume\":\"55 1\",\"pages\":\"758-767\"},\"PeriodicalIF\":8.6000,\"publicationDate\":\"2024-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Systems Man Cybernetics-Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10752413/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Systems Man Cybernetics-Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10752413/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Equivalent Piecewise Derivative Adaptive Control With Fuzzy Rules Emulated Network and Mitigation of Catastrophic Forgetting Learning
This article presents a novel adaptive control approach for a class of unknown discrete-time systems using piecewise derivatives derived from experimentally obtained input-output characteristics of the controlled plant. The control law is formulated using a multi-input fuzzy rules emulated network (MiFREN). The learning law is developed to address the issue of catastrophic forgetting, in alignment with the proposed information matrix. Closed-loop analysis demonstrates convergence of the tracking error and weight parameters under feasible conditions. Validation through experiments with a DC-motor torque control system, alongside comparative controllers, demonstrates the superior tracking performance of the proposed method and its effective mitigation of forgetting during tracking tasks.
期刊介绍:
The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.