Numerical Methods for Optimal Control Problems with State Constraints

Numerical Methods for Optimal Control Problems with State Constraints

Author: Radoslaw Pytlak

Publisher: Springer

Published: 2006-11-14

Total Pages: 224

ISBN-13: 3540486623

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While optimality conditions for optimal control problems with state constraints have been extensively investigated in the literature the results pertaining to numerical methods are relatively scarce. This book fills the gap by providing a family of new methods. Among others, a novel convergence analysis of optimal control algorithms is introduced. The analysis refers to the topology of relaxed controls only to a limited degree and makes little use of Lagrange multipliers corresponding to state constraints. This approach enables the author to provide global convergence analysis of first order and superlinearly convergent second order methods. Further, the implementation aspects of the methods developed in the book are presented and discussed. The results concerning ordinary differential equations are then extended to control problems described by differential-algebraic equations in a comprehensive way for the first time in the literature.


Optimal Control

Optimal Control

Author: Frank L. Lewis

Publisher: John Wiley & Sons

Published: 2012-02-01

Total Pages: 552

ISBN-13: 0470633492

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A NEW EDITION OF THE CLASSIC TEXT ON OPTIMAL CONTROL THEORY As a superb introductory text and an indispensable reference, this new edition of Optimal Control will serve the needs of both the professional engineer and the advanced student in mechanical, electrical, and aerospace engineering. Its coverage encompasses all the fundamental topics as well as the major changes that have occurred in recent years. An abundance of computer simulations using MATLAB and relevant Toolboxes is included to give the reader the actual experience of applying the theory to real-world situations. Major topics covered include: Static Optimization Optimal Control of Discrete-Time Systems Optimal Control of Continuous-Time Systems The Tracking Problem and Other LQR Extensions Final-Time-Free and Constrained Input Control Dynamic Programming Optimal Control for Polynomial Systems Output Feedback and Structured Control Robustness and Multivariable Frequency-Domain Techniques Differential Games Reinforcement Learning and Optimal Adaptive Control


Automatic Control 1990

Automatic Control 1990

Author: Ü Jaaksoo

Publisher: Elsevier

Published: 2014-05-23

Total Pages: 555

ISBN-13: 1483297462

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This volume provides a general overview on the state-of-the-art and future developments in automation and control. The application of systems and control in all areas is covered, from the social and cultural effects of control, to control in mineral and metal processing. This volume will be an invaluable source of information to all those interested in the areas of automation and control.


Conjugate Gradient Algorithms in Nonconvex Optimization

Conjugate Gradient Algorithms in Nonconvex Optimization

Author: Radoslaw Pytlak

Publisher: Springer Science & Business Media

Published: 2008-11-18

Total Pages: 493

ISBN-13: 354085634X

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This book details algorithms for large-scale unconstrained and bound constrained optimization. It shows optimization techniques from a conjugate gradient algorithm perspective as well as methods of shortest residuals, which have been developed by the author.


Dynamic Modelling and Control of National Economies 1989

Dynamic Modelling and Control of National Economies 1989

Author: N.M. Christodoulakis

Publisher: Elsevier

Published: 2014-06-28

Total Pages: 599

ISBN-13: 1483298825

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The Symposium aimed at analysing and solving the various problems of representation and analysis of decision making in economic systems starting from the level of the individual firm and ending up with the complexities of international policy coordination. The papers are grouped into subject areas such as game theory, control methods, international policy coordination and the applications of artificial intelligence and experts systems as a framework in economic modelling and control. The Symposium therefore provides a wide range of important information for those involved or interested in the planning of company and national economics.


Nonlinear Equations and Optimisation

Nonlinear Equations and Optimisation

Author: L.T. Watson

Publisher: Elsevier

Published: 2001-03-14

Total Pages: 382

ISBN-13: 0080929540

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/homepage/sac/cam/na2000/index.html7-Volume Set now available at special set price ! In one of the papers in this collection, the remark that "nothing at all takes place in the universe in which some rule of maximum of minimum does not appear" is attributed to no less an authority than Euler. Simplifying the syntax a little, we might paraphrase this as Everything is an optimization problem. While this might be something of an overstatement, the element of exaggeration is certainly reduced if we consider the extended form: Everything is an optimization problem or a system of equations. This observation, even if only partly true, stands as a fitting testimonial to the importance of the work covered by this volume. Since the 1960s, much effort has gone into the development and application of numerical algorithms for solving problems in the two areas of optimization and systems of equations. As a result, many different ideas have been proposed for dealing efficiently with (for example) severe nonlinearities and/or very large numbers of variables. Libraries of powerful software now embody the most successful of these ideas, and one objective of this volume is to assist potential users in choosing appropriate software for the problems they need to solve. More generally, however, these collected review articles are intended to provide both researchers and practitioners with snapshots of the 'state-of-the-art' with regard to algorithms for particular classes of problem. These snapshots are meant to have the virtues of immediacy through the inclusion of very recent ideas, but they also have sufficient depth of field to show how ideas have developed and how today's research questions have grown out of previous solution attempts. The most efficient methods for local optimization, both unconstrained and constrained, are still derived from the classical Newton approach. As well as dealing in depth with the various classical, or neo-classical, approaches, the selection of papers on optimization in this volume ensures that newer ideas are also well represented. Solving nonlinear algebraic systems of equations is closely related to optimization. The two are not completely equivalent, however, and usually something is lost in the translation. Algorithms for nonlinear equations can be roughly classified as locally convergent or globally convergent. The characterization is not perfect. Locally convergent algorithms include Newton's method, modern quasi-Newton variants of Newton's method, and trust region methods. All of these approaches are well represented in this volume.


Computational Methods for Optimizing Distributed Systems

Computational Methods for Optimizing Distributed Systems

Author: Charles Teo

Publisher: Academic Press

Published: 1984-08-21

Total Pages: 331

ISBN-13: 0080956785

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Optimal control theory of distributed parameter systems has been a very active field in recent years; however, very few books have been devoted to the studiy of computational algorithms for solving optimal control problems. For this rason the authors decided to write this book. Because the area is so broad, they confined themselves to optimal control problems involving first and second boundary-value problems of a linear second-order parabolic partial differential equation. However the techniques used are by no means restricted to these problems. They can be and in some cases already have been applied to problems involving other types of distributed parameter system. The authors aim is to devise computational algorithms for solving optimal control problems with particular emphasis on the mathematical theory underlying the algorithms. These algorithms are obtained by using a first-order strong variational method or gradient-type methods.