{"title":"Adaptive Fuzzy Inverse Optimal Output Regulation for a Class of Nonlinear Time-Delay Systems","authors":"Guizhi Meng, Yan Lv","doi":"10.1002/acs.3962","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>This paper aims to solve the adaptive fuzzy inverse optimal output regulation problem for a class of uncertain nonlinear systems with the exosystem. Both unknown nonlinear functions and time-delay are considered here. The output regulation problem is first converted into a stabilization problem by employing the internal model principle. Then, fuzzy logic systems (FLSs) are employed to approximate unknown nonlinear functions. A new cost functional related to the internal model and time-delay is established. An auxiliary system connected to time-delay is constructed, and a new fuzzy state observer based on the auxiliary system is designed to estimate the unmeasured states. Further, by utilizing the adaptive backstepping control technique, the inverse optimal control method, and the Lyapunov–Krasovskii functional, a novel adaptive fuzzy inverse optimal output feedback controller and adaptive law are presented. It is also proved that all signals of the closed-loop system are globally uniformly ultimately bounded (UUB); the proposed controller can achieve inverse optimization by minimizing the cost functional. Finally, a simulation example is provided to prove the effectiveness of the method in this paper.</p>\n </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 3","pages":"622-634"},"PeriodicalIF":3.9000,"publicationDate":"2025-01-06","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.3962","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}
引用次数: 0
Abstract
This paper aims to solve the adaptive fuzzy inverse optimal output regulation problem for a class of uncertain nonlinear systems with the exosystem. Both unknown nonlinear functions and time-delay are considered here. The output regulation problem is first converted into a stabilization problem by employing the internal model principle. Then, fuzzy logic systems (FLSs) are employed to approximate unknown nonlinear functions. A new cost functional related to the internal model and time-delay is established. An auxiliary system connected to time-delay is constructed, and a new fuzzy state observer based on the auxiliary system is designed to estimate the unmeasured states. Further, by utilizing the adaptive backstepping control technique, the inverse optimal control method, and the Lyapunov–Krasovskii functional, a novel adaptive fuzzy inverse optimal output feedback controller and adaptive law are presented. It is also proved that all signals of the closed-loop system are globally uniformly ultimately bounded (UUB); the proposed controller can achieve inverse optimization by minimizing the cost functional. Finally, a simulation example is provided to prove the effectiveness of the method in this paper.
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.