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1. |
Record Nr. |
UNINA9910254202103321 |
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Autore |
Prodan Ionela |
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Titolo |
Mixed-integer representations in control design : mathematical foundations and applications / / by Ionela Prodan, Florin Stoican, Sorin Olaru, Silviu-Iulian Niculescu |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (115 p.) |
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Collana |
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SpringerBriefs in Control, Automation and Robotics, , 2192-6786 |
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Disciplina |
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Soggetti |
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Automatic control |
System theory |
Calculus of variations |
Robotics |
Automation |
Control and Systems Theory |
Systems Theory, Control |
Calculus of Variations and Optimal Control; Optimization |
Robotics and Automation |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters and index. |
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Nota di contenuto |
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Introduction -- Non-Covex Region Characterization by Hyperplane Arrangements -- Mixed-Integer Representations -- Examples of Multi-Agent Control Problems -- Conclusions. |
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Sommario/riassunto |
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In this book, the authors propose efficient characterizations of the non-convex regions that appear in many control problems, such as those involving collision/obstacle avoidance and, in a broader sense, in the description of feasible sets for optimization-based control design involving contradictory objectives. The text deals with a large class of systems that require the solution of appropriate optimization problems over a feasible region, which is neither convex nor compact. The proposed approach uses the combinatorial notion of hyperplane arrangement, partitioning the space by a finite collection of |
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hyperplanes, to describe non-convex regions efficiently. Mixed-integer programming techniques are then applied to propose acceptable formulations of the overall problem. Multiple constructions may arise from the same initial problem, and their complexity under various parameters - space dimension, number of binary variables, etc. - is also discussed. This book is a useful tool for academic researchers and graduate students interested in non-convex systems working in control engineering area, mobile robotics and/or optimal planning and decision-making. |
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