{"title":"二阶随机非线性多代理系统的自适应有限时间最优时变编队控制","authors":"Jiaxin Zhang, Yue Fu, Jun Fu","doi":"10.1002/acs.3788","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>This work addresses a fuzzy-based finite-time optimal time-varying formation (TVF) control issue for a class of second-order stochastic multi-agent systems (SMASs) with unknown nonlinearities. First, novel optimal cost functions with exponential power terms are constructed, which enables the SMASs to achieve finite-time stability in the mean square sense with minimum cost. Then, based on the cost functions, an optimal controller is proposed, in which fuzzy logic systems (FLSs) are used as universal approximators to identify the unknown uncertainties. Theorem analyses show that the proposed control strategy can guarantee the mean-square finite-time bounded of all signals in the system and then the TVF control task can be simultaneously realized with minimum cost. Finally, the effectiveness of the presented control method is verified by a multiple omni-directional robot system.</p>\n </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 6","pages":"2022-2044"},"PeriodicalIF":3.9000,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive finite-time optimal time-varying formation control for second-order stochastic nonlinear multiagent systems\",\"authors\":\"Jiaxin Zhang, Yue Fu, Jun Fu\",\"doi\":\"10.1002/acs.3788\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>This work addresses a fuzzy-based finite-time optimal time-varying formation (TVF) control issue for a class of second-order stochastic multi-agent systems (SMASs) with unknown nonlinearities. First, novel optimal cost functions with exponential power terms are constructed, which enables the SMASs to achieve finite-time stability in the mean square sense with minimum cost. Then, based on the cost functions, an optimal controller is proposed, in which fuzzy logic systems (FLSs) are used as universal approximators to identify the unknown uncertainties. Theorem analyses show that the proposed control strategy can guarantee the mean-square finite-time bounded of all signals in the system and then the TVF control task can be simultaneously realized with minimum cost. Finally, the effectiveness of the presented control method is verified by a multiple omni-directional robot system.</p>\\n </div>\",\"PeriodicalId\":50347,\"journal\":{\"name\":\"International Journal of Adaptive Control and Signal Processing\",\"volume\":\"38 6\",\"pages\":\"2022-2044\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-03-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Adaptive Control and Signal Processing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/acs.3788\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Adaptive Control and Signal Processing","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/acs.3788","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Adaptive finite-time optimal time-varying formation control for second-order stochastic nonlinear multiagent systems
This work addresses a fuzzy-based finite-time optimal time-varying formation (TVF) control issue for a class of second-order stochastic multi-agent systems (SMASs) with unknown nonlinearities. First, novel optimal cost functions with exponential power terms are constructed, which enables the SMASs to achieve finite-time stability in the mean square sense with minimum cost. Then, based on the cost functions, an optimal controller is proposed, in which fuzzy logic systems (FLSs) are used as universal approximators to identify the unknown uncertainties. Theorem analyses show that the proposed control strategy can guarantee the mean-square finite-time bounded of all signals in the system and then the TVF control task can be simultaneously realized with minimum cost. Finally, the effectiveness of the presented control method is verified by a multiple omni-directional robot system.
期刊介绍：
The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material.
Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include:
Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers
Nonlinear, Robust and Intelligent Adaptive Controllers
Linear and Nonlinear Multivariable System Identification and Estimation
Identification of Linear Parameter Varying, Distributed and Hybrid Systems
Multiple Model Adaptive Control
Adaptive Signal processing Theory and Algorithms
Adaptation in Multi-Agent Systems
Condition Monitoring Systems
Fault Detection and Isolation Methods
Fault Detection and Isolation Methods
Fault-Tolerant Control (system supervision and diagnosis)
Learning Systems and Adaptive Modelling
Real Time Algorithms for Adaptive Signal Processing and Control
Adaptive Signal Processing and Control Applications
Adaptive Cloud Architectures and Networking
Adaptive Mechanisms for Internet of Things
Adaptive Sliding Mode Control.
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