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001 978-3-319-26995-5
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020 _a9783319269955
_9978-3-319-26995-5
024 7 _a10.1007/978-3-319-26995-5
_2doi
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aGPFC
_2bicssc
072 7 _aTEC004000
_2bisacsh
072 7 _aTJFM
_2thema
082 0 4 _a629.8312
_223
082 0 4 _a003
_223
100 1 _aProdan, Ionela.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_961974
245 1 0 _aMixed-Integer Representations in Control Design
_h[electronic resource] :
_bMathematical Foundations and Applications /
_cby Ionela Prodan, Florin Stoican, Sorin Olaru, Silviu-Iulian Niculescu.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXII, 107 p. 30 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Control, Automation and Robotics,
_x2192-6794
505 0 _aIntroduction -- Non-Covex Region Characterization by Hyperplane Arrangements -- Mixed-Integer Representations -- Examples of Multi-Agent Control Problems -- Conclusions.
520 _aIn 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.
650 0 _aControl engineering.
_931970
650 0 _aSystem theory.
_93409
650 0 _aControl theory.
_93950
650 0 _aMathematical optimization.
_94112
650 0 _aCalculus of variations.
_917382
650 0 _aRobotics.
_92393
650 0 _aAutomation.
_92392
650 1 4 _aControl and Systems Theory.
_931972
650 2 4 _aSystems Theory, Control .
_931597
650 2 4 _aCalculus of Variations and Optimization.
_931596
650 2 4 _aControl, Robotics, Automation.
_931971
700 1 _aStoican, Florin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_961975
700 1 _aOlaru, Sorin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_961976
700 1 _aNiculescu, Silviu-Iulian.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_961977
710 2 _aSpringerLink (Online service)
_961978
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319269931
776 0 8 _iPrinted edition:
_z9783319269948
830 0 _aSpringerBriefs in Control, Automation and Robotics,
_x2192-6794
_961979
856 4 0 _uhttps://doi.org/10.1007/978-3-319-26995-5
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c80869
_d80869