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Robust model predictive control for nonlinear discrete‐time systems
Author(s) -
Magni L.,
De Nicolao G.,
Scattolini R.,
Allgöwer F.
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.815
Subject(s) - model predictive control , control theory (sociology) , nonlinear system , bounded function , discrete time and continuous time , horizon , stability (learning theory) , computer science , robust control , class (philosophy) , control (management) , state (computer science) , mathematical optimization , mathematics , algorithm , artificial intelligence , physics , quantum mechanics , mathematical analysis , statistics , geometry , machine learning
This paper describes a model predictive control (MPC) algorithm for the solution of a state‐feedback robust control problem for discrete‐time nonlinear systems. The control law is obtained through the solution of a finite‐horizon dynamic game and guarantees robust stability in the face of a class of bounded disturbances and/or parameter uncertainties. A simulation example is reported to show the applicability of the method. Copyright © 2003 John Wiley & Sons, Ltd.