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Springer Vieweg - IT & Informatik - Praktische Informatik | Fast Numerical Methods for Mixed-Integer Nonlinear Model-Predictive Control

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

Kirches, Christian

2011, XX, 367p. 64 illus..

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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.

Content Level » Research

Keywords » Nichtlineare Optimierung - Optimale Steuerung - gemischt-ganzzahlige Optimierung - nichtlineare modell-prädiktive Regelung - optimal control

Related subjects » Praktische Informatik

Table of contents 

The Direct Multiple Shooting Method for Optimal Control - Mixed-Integer Optimal Control - Constrained Nonlinear Programming - Mixed-Integer Real-Time Iterations - Outer Convexification of Constraints - A Nonconvex Parametric SQP Method - Linear Algebra for Block Structured QPs - Updates for the Block Structured Factorization

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