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Output feedback stabilization of constrained systems with nonlinear predictive control
Author(s) -
Findeisen Rolf,
Imsland Lars,
Allgöwer Frank,
Foss Bjarne A.
Publication year - 2003
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.814
Subject(s) - control theory (sociology) , model predictive control , nonlinear system , controller (irrigation) , observer (physics) , sampling (signal processing) , mimo , computer science , stability (learning theory) , full state feedback , state (computer science) , nonlinear control , mathematics , control (management) , algorithm , artificial intelligence , detector , physics , quantum mechanics , telecommunications , computer network , channel (broadcasting) , machine learning , agronomy , biology
We present an output feedback stabilization scheme for uniformly completely observable nonlinear MIMO systems combining nonlinear model predictive control (NMPC) and high‐gain observers. The control signal is recalculated at discrete sampling instants by an NMPC controller using a system model for the predictions. The state information necessary for the prediction is provided by a continuous time high‐gain observer. The resulting ‘optimal’ control signal is open‐loop implemented until the next sampling instant. With the proposed scheme semi‐global practical stability is achieved. That is, for initial conditions in any compact set contained in the region of attraction of the NMPC state feedback controller, the system states will enter any small set containing the origin, if the high‐gain observers is sufficiently fast and the sampling time is small enough. In principle the proposed approach can be used for a variety of state feedback NMPC schemes. Copyright © 2003 John Wiley & Sons, Ltd.