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Stabilizing conditions for model predictive control
Author(s) -
Mayne David Q.,
Falugi Paola
Publication year - 2018
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.4409
Subject(s) - model predictive control , cover (algebra) , constraint (computer aided design) , range (aeronautics) , computer science , stability (learning theory) , control (management) , mathematical optimization , control theory (sociology) , engineering , mathematics , artificial intelligence , machine learning , mechanical engineering , aerospace engineering
Summary Existing stabilizing conditions that use a terminal cost and constraint that, if satisfied, ensure stability and recursive feasibility for deterministic, robust, and stochastic model predictive control are briefly reviewed and analyzed. It is pointed out that these conditions do not cover all situations. Proposals are made to cover a wider range of desired applications.