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A stabilizing real-time implementation of nonlinear model predictive control. (English) Zbl 1226.93065
Biegler, Lorenz T. (ed.) et al., Real-time PDE-constrained optimization. Philadelphia, PA: Society for Industrial and Applied Mathematics (SIAM) (ISBN 978-0-898716-21-4/pbk; 978-0-89871-893-5/ebook). Computational Science & Engineering, 25-52 (2007).
From the introduction: Nonlinear Model Predictive Control (NMPC) is a feedback control technique based on the real-time solution of optimal control problems.
The principal aim of the chapter is to prove that for the real-time iteration scheme the closed loop consisting of the combined system-optimizer dynamics is stable under certain conditions. The investigation combines concepts from both classical stability theory for NMPC as well as from convergence theory for Newton-type optimization methods.
For the entire collection see [Zbl 1117.49004].

MSC:
93B52 Feedback control
93B51 Design techniques (robust design, computer-aided design, etc.)
93B40 Computational methods in systems theory (MSC2010)
93D15 Stabilization of systems by feedback
49M15 Newton-type methods
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