04381nam 22007695 450 991025420210332120221021220141.03-319-26995-X10.1007/978-3-319-26995-5(CKB)3710000000532202(EBL)4178580(SSID)ssj0001584680(PQKBManifestationID)16264542(PQKBTitleCode)TC0001584680(PQKBWorkID)14864334(PQKB)10012066(DE-He213)978-3-319-26995-5(MiAaPQ)EBC4178580(PPN)190523336(EXLCZ)99371000000053220220151125d2016 u| 0engur|n|---|||||txtccrMixed-integer representations in control design mathematical foundations and applications /by Ionela Prodan, Florin Stoican, Sorin Olaru, Silviu-Iulian Niculescu1st ed. 2016.Cham :Springer International Publishing :Imprint: Springer,2016.1 online resource (115 p.)SpringerBriefs in Control, Automation and Robotics,2192-6786Description based upon print version of record.3-319-26993-3 Includes bibliographical references at the end of each chapters and index.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.SpringerBriefs in Control, Automation and Robotics,2192-6786Control engineeringSystem theoryCalculus of variationsRoboticsAutomationControl and Systems Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/T19010Systems Theory, Controlhttps://scigraph.springernature.com/ontologies/product-market-codes/M13070Calculus of Variations and Optimal Control; Optimizationhttps://scigraph.springernature.com/ontologies/product-market-codes/M26016Robotics and Automationhttps://scigraph.springernature.com/ontologies/product-market-codes/T19020Control engineering.System theory.Calculus of variations.Robotics.Automation.Control and Systems Theory.Systems Theory, Control.Calculus of Variations and Optimal Control; Optimization.Robotics and Automation.629.8312Prodan Ionelaauthttp://id.loc.gov/vocabulary/relators/aut1061088Stoican Florinauthttp://id.loc.gov/vocabulary/relators/autOlaru Sorinauthttp://id.loc.gov/vocabulary/relators/autNiculescu Silviu-Iulianauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910254202103321Mixed-Integer Representations in Control Design2517418UNINA