This work provides a real-time algorithmic optimal control framework for autonomous switched systems. Traditional optimal control approaches for autonomous switched systems are open-loop in nature. Therefore, the switching times of the system can not be adjusted or adapted when the system parameters or the operational environments change. This work aims to close this loop, and apply adaptations to the optimal switching strategy based on new information that can only be captured on-line. One important contribution of this work is to provide the means to allow feedback (in a general sense) to the control laws (i.e. the switching times) of the switched system so that the control laws can be updated to maintain optimality of the switching-time control inputs. Furthermore, convergence analysis for the proposed algorithms are presented. The effectiveness of the real-time algorithms is demonstrated by an application in optimal formation and coverage control of a networked system. This application is implemented on a realistic simulation framework consisting of a number of Unmanned Aerial Vehicles (UAVs) that interact in a virtual 3D world.
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Xu Chu Ding received his B.S., M.S. and Ph.D. degree in Electrical and Computer Engineering from the Georgia Institute of Technology, Atlanta, in 2004, 2007 and 2009, respectively. His research interests include optimal control of hybrid systems and intelligent and persistent surveillance with a network of mobile agents.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work provides a real-time algorithmic optimal control framework for autonomous switched systems. Traditional optimal control approaches for autonomous switched systems are open-loop in nature. Therefore, the switching times of the system can not be adjusted or adapted when the system parameters or the operational environments change. This work aims to close this loop, and apply adaptations to the optimal switching strategy based on new information that can only be captured on-line. One important contribution of this work is to provide the means to allow feedback (in a general sense) to the control laws (i.e. the switching times) of the switched system so that the control laws can be updated to maintain optimality of the switching-time control inputs. Furthermore, convergence analysis for the proposed algorithms are presented. The effectiveness of the real-time algorithms is demonstrated by an application in optimal formation and coverage control of a networked system. This application is implemented on a realistic simulation framework consisting of a number of Unmanned Aerial Vehicles (UAVs) that interact in a virtual 3D world. 148 pp. Englisch. Bestandsnummer des Verkäufers 9783838398006
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ding Xu ChuXu Chu Ding received his B.S., M.S. and Ph.D. degree in Electrical and Computer Engineering from the Georgia Institute of Technology, Atlanta, in 2004, 2007 and 2009, respectively. His research interests include optimal co. Bestandsnummer des Verkäufers 5420014
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This work provides a real-time algorithmic optimal control framework for autonomous switched systems. Traditional optimal control approaches for autonomous switched systems are open-loop in nature. Therefore, the switching times of the system can not be adjusted or adapted when the system parameters or the operational environments change. This work aims to close this loop, and apply adaptations to the optimal switching strategy based on new information that can only be captured on-line. One important contribution of this work is to provide the means to allow feedback (in a general sense) to the control laws (i.e. the switching times) of the switched system so that the control laws can be updated to maintain optimality of the switching-time control inputs. Furthermore, convergence analysis for the proposed algorithms are presented. The effectiveness of the real-time algorithms is demonstrated by an application in optimal formation and coverage control of a networked system. This application is implemented on a realistic simulation framework consisting of a number of Unmanned Aerial Vehicles (UAVs) that interact in a virtual 3D world.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 148 pp. Englisch. Bestandsnummer des Verkäufers 9783838398006
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work provides a real-time algorithmic optimal control framework for autonomous switched systems. Traditional optimal control approaches for autonomous switched systems are open-loop in nature. Therefore, the switching times of the system can not be adjusted or adapted when the system parameters or the operational environments change. This work aims to close this loop, and apply adaptations to the optimal switching strategy based on new information that can only be captured on-line. One important contribution of this work is to provide the means to allow feedback (in a general sense) to the control laws (i.e. the switching times) of the switched system so that the control laws can be updated to maintain optimality of the switching-time control inputs. Furthermore, convergence analysis for the proposed algorithms are presented. The effectiveness of the real-time algorithms is demonstrated by an application in optimal formation and coverage control of a networked system. This application is implemented on a realistic simulation framework consisting of a number of Unmanned Aerial Vehicles (UAVs) that interact in a virtual 3D world. Bestandsnummer des Verkäufers 9783838398006
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Taschenbuch. Zustand: Neu. Real-time Optimal Control of Autonomous Switched Systems | Theory, Algorithms and Robotic Applications | Xu Chu Ding | Taschenbuch | 148 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838398006 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 107305085
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