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Robust Execution for Stochastic Hybrid Systems: Algorithms for Control, Estimation and Learning - Softcover

 
9783639098006: Robust Execution for Stochastic Hybrid Systems: Algorithms for Control, Estimation and Learning

Inhaltsangabe

Unmanned systems, such as Autonomous Underwater Vehicles (AUVs), planetary rovers and space probes, have enormous potential in areas such as reconnaissance and space exploration. However the effectiveness and robustness of these systems is currently restricted by a lack of autonomy. A model-based executive, which increases the level of autonomy can be used to simplify the operator¿s task and leave degrees of freedom in the plan that allow the executive to optimize resources and ensure robustness to uncertainty. Uncertainty arises due to uncertain state estimation, disturbances, model uncertainty and component failures. This book develops a model-based executive that reasons explicitly from a stochastic hybrid discrete-continuous system model to find the optimal course of action, while ensuring the required level of robustness to uncertainty is achieved. The executive makes use of new algorithms for control, estimation and learning of stochastic systems, which are presented in this book.

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Reseña del editor

Unmanned systems, such as Autonomous Underwater Vehicles (AUVs), planetary rovers and space probes, have enormous potential in areas such as reconnaissance and space exploration. However the effectiveness and robustness of these systems is currently restricted by a lack of autonomy. A model-based executive, which increases the level of autonomy can be used to simplify the operator's task and leave degrees of freedom in the plan that allow the executive to optimize resources and ensure robustness to uncertainty. Uncertainty arises due to uncertain state estimation, disturbances, model uncertainty and component failures. This book develops a model-based executive that reasons explicitly from a stochastic hybrid discrete-continuous system model to find the optimal course of action, while ensuriang the required level of robustness to uncertainty is achieved. The executive makes use of new algorithms for control, estimation and learning of stochastic systems, which are presented in this book.

Biografía del autor

Lars has a Ph.D. in Control and Estimation from the Massachusetts Institute of Technology, where he was supervised by Prof. Brian Williams. He has B.A. and M.Eng. degrees from the University of Cambridge, supervised by Prof. Keith Glover. He is now with the Guidance and Control Analysis Group at the NASA Jet Propulsion Laboratory.

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Blackmore, Lars
Verlag: VDM Verlag Dr. Müller, 2008
ISBN 10: 3639098005 ISBN 13: 9783639098006
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Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Unmanned systems, such as Autonomous Underwater Vehicles (AUVs), planetary rovers and space probes, haveenormous potential in areas such as reconnaissance and spaceexploration. However the effectiveness and robustness of these . Bestandsnummer des Verkäufers 4957197

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