Language: English
Published by Springer Verlag; Berlin, 1970
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Published by Cambridge University Press, 1999
ISBN 10: 0521645573 ISBN 13: 9780521645577
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Paperback. Condition: New. Using material from many different sources in a systematic and unified way, this self-contained book provides both rigorous mathematical theory and practical numerical insights while developing a framework for determining the convergence rate of discrete approximations to optimal control problems. Elements of the framework include the reference point, the truncation error, and a stability theory for the linearized first-order optimality conditions.Within this framework, the discretized control problem has a stationary point whose distance to the reference point is bounded in terms of the truncation error. The theory applies to a broad range of discretizations and provides completely new insights into the convergence theory for discrete approximations in optimal control, including the relationship between orthogonal collocation and Runge-Kutta methods.Throughout the book, derivatives associated with the discretized control problem are expressed in terms of a back-propagated costate. In particular, the objective derivative of a bang-bang or singular control problem with respect to a switch point of the control are obtained, which leads to the efficient solution of a class of nonsmooth control problems using a gradient-based optimizer.
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ISBN 10: 1611978254 ISBN 13: 9781611978254
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Published by Society for Industrial & Applied Mathematics,U.S., 2025
ISBN 10: 1611978254 ISBN 13: 9781611978254
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Language: English
Published by Cambridge University Press, 1999
ISBN 10: 0521645573 ISBN 13: 9780521645577
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Published by Society for Industrial & Applied Mathematics,U.S., 2025
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Language: English
Published by Springer Berlin Heidelberg, 1970
ISBN 10: 3540049517 ISBN 13: 9783540049517
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The purpose of this modest report is to present in a simplified manner some of the computational methods that have been developed in the last ten years for the solution of optimal control problems. Only those methods that are based on the minimum (maximum) principle of Pontriagin are discussed here. The autline of the report is as follows: In the first two sections a control problem of Bolza is formulated and the necessary conditions in the form of the minimum principle are given. The method of steepest descent and a conjugate gradient-method are dis cussed in Section 3. In the remaining sections, the successive sweep method, the Newton-Raphson method and the generalized Newton-Raphson method (also called quasilinearization method) ar~ presented from a unified approach which is based on the application of Newton Raphson approximation to the necessary conditions of optimality. The second-variation method and other shooting methods based on minimizing an error function are also considered. TABLE OF CONTENTS 1. 0 INTRODUCTION 1 2. 0 NECESSARY CONDITIONS FOR OPTIMALITY -------- 2 3. 0 THE GRADIENT METHOD 4 3. 1 Min H Method and Conjugate Gradient Method -. ---------. . . . ------. --------. - 8 3. 2 Boundary Constraints -----------. ----. - 9 3. 3 Problems with Control Constraints --. -- 15 4. 0 SUCCESSIVE SWEEP METHOD -------------------- 18 4. 1 Final Time Given Implicitly ----. ------ 22 5. 0 SECOND-VARIATION METHOD -------------------- 23 6. 0 SHOOTING METHODS --------------------------- 27 6. 1 Newton-RaphsonMethod ----------------- 27 6.
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Published by Society for Industrial and Applied Mathematics,U.S., US, 2025
ISBN 10: 1611978254 ISBN 13: 9781611978254
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Add to basketPaperback. Condition: New. Using material from many different sources in a systematic and unified way, this self-contained book provides both rigorous mathematical theory and practical numerical insights while developing a framework for determining the convergence rate of discrete approximations to optimal control problems. Elements of the framework include the reference point, the truncation error, and a stability theory for the linearized first-order optimality conditions.Within this framework, the discretized control problem has a stationary point whose distance to the reference point is bounded in terms of the truncation error. The theory applies to a broad range of discretizations and provides completely new insights into the convergence theory for discrete approximations in optimal control, including the relationship between orthogonal collocation and Runge-Kutta methods.Throughout the book, derivatives associated with the discretized control problem are expressed in terms of a back-propagated costate. In particular, the objective derivative of a bang-bang or singular control problem with respect to a switch point of the control are obtained, which leads to the efficient solution of a class of nonsmooth control problems using a gradient-based optimizer.