{"title":"List of Figures and Tables","authors":"","doi":"10.1515/9780691203317-001","DOIUrl":"https://doi.org/10.1515/9780691203317-001","url":null,"abstract":"","PeriodicalId":201486,"journal":{"name":"Delay-Adaptive Linear Control","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127048212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Frontmatter","authors":"","doi":"10.1515/9780691203317-fm","DOIUrl":"https://doi.org/10.1515/9780691203317-fm","url":null,"abstract":"","PeriodicalId":201486,"journal":{"name":"Delay-Adaptive Linear Control","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126109269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Single-Input Systems with Full Relative Degree","authors":"Yang Zhu, M. Krstić","doi":"10.2307/j.ctvrf8c6w.10","DOIUrl":"https://doi.org/10.2307/j.ctvrf8c6w.10","url":null,"abstract":"This chapter analyzes single-input systems with full relative degree. The primary approach is based on the adaptive backstepping control with Kreisselmeier-filters. In output-feedback adaptive problems, the relative degree plays a major role in determining the difficulty of a problem. The chapter focuses on a special class of LTI systems with its relative degree being equal to its system dimension. Moreover, in this chapter the actuator state is assumed to be measured. The chapter also presents a combination of prediction-based boundary control with adaptive backstepping to address unknown parameters and time delay. It then develops two Lyapunov-based identifiers to estimate unknown plant parameters and actuator time delay.","PeriodicalId":201486,"journal":{"name":"Delay-Adaptive Linear Control","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128236035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Basic Predictor Feedback for Single-Input Systems","authors":"Yang Zhu, M. Krstić","doi":"10.2307/j.ctvrf8c6w.8","DOIUrl":"https://doi.org/10.2307/j.ctvrf8c6w.8","url":null,"abstract":"This chapter discusses the basic idea of a partial differential equation (PDE) backstepping approach for single-input LTI ordinary differential equation (ODE) systems with discrete input delay. The key point of the backstepping approach lies in it providing a systematic construction of an infinite-dimensional transformation of the actuator state, which yields a cascade system of transformed stable actuator dynamics and stabilized plant dynamics. The cascade system consisting of such infinite-dimensional stable actuator dynamics and finite-dimensional stabilized plant dynamics is referred to as the closed-loop “target system.” The chapter first presents an alternative view of the backstepping transformation based purely on standard ODE delay notation. Then the backstepping transformation is described in PDE and rescaled unity-interval transport PDE notation.","PeriodicalId":201486,"journal":{"name":"Delay-Adaptive Linear Control","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114464401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Chapter Seven. Full-State Feedback of Uncertain Multi-Input Systems","authors":"Yang Zhu, M. Krstić","doi":"10.1515/9780691203317-011","DOIUrl":"https://doi.org/10.1515/9780691203317-011","url":null,"abstract":"This chapter investigates adaptive control for uncertain multi-input LTI systems with distinct discrete actuator delays. In parallel with the single-input case in the third chapter, four types of basic uncertainties come with multi-input LTI time-delay systems. Different combinations of the four uncertainties above result in different design difficulties. For example, when the full-state measurement of the transport PDE state is available, the global stabilization is acquired, whereas when the actuator state is not measurable and the delay value is unknown at the same time, the problem is not solvable globally, since the problem is not linearly parameterized. The chapter then summarizes the different collections of uncertainties for the multi-input case. When some of the four variables are unknown or unmeasured, the basic idea of certainty-equivalence-based adaptive control is to use an estimator (a parameter estimator or a state estimator) to replace the unknown variables in the PDE-based framework in the previous chapter, and carefully select their adaptive update laws based on Lyapunov-based analysis.","PeriodicalId":201486,"journal":{"name":"Delay-Adaptive Linear Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130400347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Chapter Three. Basic Idea of Adaptive Control for Single-Input Systems","authors":"Yang Zhu, M. Krstić","doi":"10.1515/9780691203317-007","DOIUrl":"https://doi.org/10.1515/9780691203317-007","url":null,"abstract":"This chapter provides a variety of adaptive predictor control techniques to deal with different uncertainty collections from four basic uncertainties. These include delay, parameter, ODE state, and PDE state. In the presence of a discrete actuator delay that is long and unknown, but when the actuator state is available for measurement, a global adaptive stabilization result is obtainable. In contrast, the problem where the delay value is unknown, and where the actuator state is not measurable at the same time, is not solvable globally, since the problem is not linearly parameterized in the unknown delay. In this case, a local stabilization is feasible, with restrictions on the initial conditions such that not only do the initial values of the ODE and actuator state have to be small, but also the initial value of the delay estimation error has to be small (the delay value is allowed to be large but the initial value of its estimate has to be close to the true value of the delay).","PeriodicalId":201486,"journal":{"name":"Delay-Adaptive Linear Control","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134534634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Predictor Feedback of Uncertain Multi-Input Systems","authors":"Yang Zhu, M. Krstić","doi":"10.2307/j.ctvrf8c6w.18","DOIUrl":"https://doi.org/10.2307/j.ctvrf8c6w.18","url":null,"abstract":"This chapter discusses the predictor feedback for uncertain multi-input systems. This is based on the predictor feedback framework for uncertainty-free multi-input systems in the tenth chapter. The chapter addresses four combinations of the five uncertainties that come from a finite-dimensional multi-input linear system with distributed actuator delays. These uncertainties include the following types: unknown and distinct delays, unknown delay kernels, unknown system matrix, unmeasurable finite-dimensional plant state, and unmeasurable infinite-dimensional actuator state. The chapter then examines the adaptive state feedback under unknown as well as uncertain delays, delay kernels, and parameters. It also explores robust output feedback under unknown delays, delay kernels, and PDE or ODE states.","PeriodicalId":201486,"journal":{"name":"Delay-Adaptive Linear Control","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129615572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
求助内容：
应助结果提醒方式：