Fast Numerical Methods for Mixed-Integer Nonlinear Model-Predictive Control

Christian Kirches

ISBN 10: 3834815721 / ISBN 13: 9783834815729

Editore: Vieweg+Teubner Verlag, 2011

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Druck auf Anfrage Neuware - Printed after ordering - Current industrial practice knows many optimization tasks that can be cast as mixed-integer optimal control problems. Due to the combinatorial character of these problems, the computation of optimal solutions under real-time constraints is still a demanding challenge.Starting with Bock's direct multiple shooting method for optimal control, Christian Kirches develops a fast numerical algorithm of wide applicability that efficiently solves mixed-integer nonlinear optimal control problems. He uses convexification and relaxation techniques to obtain computationally tractable reformulations for which feasibility and optimality certificates can be given even after discretization and rounding. In a sequential quadratic programming framework, extensive exploitation of arising structures in an active set method ultimately brings the developed algorithm towards real-time feasibility.

Codice articolo 9783834815729

Dati bibliografici

• Titolo: Fast Numerical Methods for Mixed-Integer Nonlinear Model-Predictive Control
• Editore: Vieweg+Teubner Verlag
• Data di pubblicazione: 2011
• Lingua: Inglese
• ISBN 10: 3834815721
• ISBN 13: 9783834815729
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 210 L x 148 A x 21 P (millimetri) 210 millimetri di larghezza per 148 millimetri di altezza per 21 millimetri di profondità
• Peso: 501 grammi

Descrizione articolo

Riassunto

Current industrial practice knows many optimization tasks that can be cast as mixed-integer optimal control problems. Due to the combinatorial character of these problems, the computation of optimal solutions under real-time constraints is still a demanding challenge.

Starting with Bock's direct multiple shooting method for optimal control, Christian Kirches develops a fast numerical algorithm of wide applicability that efficiently solves mixed-integer nonlinear optimal control problems. He uses convexification and relaxation techniques to obtain computationally tractable reformulations for which feasibility and optimality certificates can be given even after discretization and rounding. In a sequential quadratic programming framework, extensive exploitation of arising structures in an active set method ultimately brings the developed algorithm towards real-time feasibility.

Informazioni sull?autore

Dr. Christian Kirches is a postdoctoral researcher in the simulation and optimization group at the chair of Professor Dr. Dr. h.c. Hans Georg Bock at the Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University.