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Mixed-integer representations in con...

Prodan, Ionela.

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Mixed-integer representations in control design = mathematical foundations and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Mixed-integer representations in control design/ by Ionela Prodan ... [et al.].
Reminder of title:	mathematical foundations and applications /
other author:	Prodan, Ionela.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xii, 107 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Non-Covex Region Characterization by Hyperplane Arrangements -- Mixed-Integer Representations -- Examples of Multi-Agent Control Problems -- Conclusions.
Contained By:	Springer eBooks
Subject:	Engineering. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-26995-5
ISBN:	9783319269955$q(electronic bk.)

Mixed-integer representations in control design = mathematical foundations and applications /
Mixed-integer representations in control designmathematical foundations and applications /[electronic resource] :by Ionela Prodan ... [et al.]. - Cham :Springer International Publishing :2016. - xii, 107 p. :ill., digital ;24 cm. - SpringerBriefs in electrical and computer engineering,2191-8112. - SpringerBriefs in electrical and computer engineering..

Introduction -- Non-Covex Region Characterization by Hyperplane Arrangements -- Mixed-Integer Representations -- Examples of Multi-Agent Control Problems -- Conclusions.

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 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.

ISBN: 9783319269955$q(electronic bk.)

Standard No.: 10.1007/978-3-319-26995-5doiSubjects--Topical Terms:

586835
Engineering.

LC Class. No.: QA402.3

Dewey Class. No.: 629.8

Mixed-integer representations in control design = mathematical foundations and applications /
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245 0 0 $a Mixed-integer representations in control design $h [electronic resource] : $b mathematical foundations and applications / $c by Ionela Prodan ... [et al.].
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490 1 $a SpringerBriefs in electrical and computer engineering, $x 2191-8112
505 0 $a Introduction -- Non-Covex Region Characterization by Hyperplane Arrangements -- Mixed-Integer Representations -- Examples of Multi-Agent Control Problems -- Conclusions.
520 $a 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 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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