{"title":"一大类系统自适应控制的内在鲁棒性","authors":"Mohamad T. Shahab, Daniel E. Miller","doi":"10.1002/acs.3813","DOIUrl":null,"url":null,"abstract":"<p>Recently it has been shown how to carry out adaptive control for a linear time-invariant (LTI) plant so that the effect of the initial condition decays exponentially to zero and so that the input-output behavior enjoys a convolution bound. This, in turn, has been leveraged to prove, in several special cases, that the closed-loop system is robust in the sense that both of these properties are maintained in the presence of a small amount of parameter time-variation and unmodelled dynamics. This paper shows that this robustness property is true for a general adaptive controller with the right properties: if we are able to prove exponential stability and a convolution bound for the case of fixed plant parameters, then robustness comes for free. We also apply the results to solutions to various adaptive control problems in the literature.</p>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 7","pages":"2423-2442"},"PeriodicalIF":3.9000,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Inherent robustness in the adaptive control of a large class of systems\",\"authors\":\"Mohamad T. Shahab, Daniel E. Miller\",\"doi\":\"10.1002/acs.3813\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Recently it has been shown how to carry out adaptive control for a linear time-invariant (LTI) plant so that the effect of the initial condition decays exponentially to zero and so that the input-output behavior enjoys a convolution bound. This, in turn, has been leveraged to prove, in several special cases, that the closed-loop system is robust in the sense that both of these properties are maintained in the presence of a small amount of parameter time-variation and unmodelled dynamics. This paper shows that this robustness property is true for a general adaptive controller with the right properties: if we are able to prove exponential stability and a convolution bound for the case of fixed plant parameters, then robustness comes for free. We also apply the results to solutions to various adaptive control problems in the literature.</p>\",\"PeriodicalId\":50347,\"journal\":{\"name\":\"International Journal of Adaptive Control and Signal Processing\",\"volume\":\"38 7\",\"pages\":\"2423-2442\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-04-23\",\"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.3813\",\"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.3813","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}
Inherent robustness in the adaptive control of a large class of systems
Recently it has been shown how to carry out adaptive control for a linear time-invariant (LTI) plant so that the effect of the initial condition decays exponentially to zero and so that the input-output behavior enjoys a convolution bound. This, in turn, has been leveraged to prove, in several special cases, that the closed-loop system is robust in the sense that both of these properties are maintained in the presence of a small amount of parameter time-variation and unmodelled dynamics. This paper shows that this robustness property is true for a general adaptive controller with the right properties: if we are able to prove exponential stability and a convolution bound for the case of fixed plant parameters, then robustness comes for free. We also apply the results to solutions to various adaptive control problems in the literature.
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.