Premium
Robust predictive control of switched systems: Satisfying uncertain schedules subject to state and control constraints
Author(s) -
Mhaskar Prashant,
ElFarra Nael H.,
Christofides Panagiotis D.
Publication year - 2008
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.975
Subject(s) - model predictive control , control theory (sociology) , schedule , parametric statistics , constraint (computer aided design) , computer science , constraint satisfaction , mathematical optimization , state (computer science) , control (management) , stability (learning theory) , sequence (biology) , nonlinear system , set (abstract data type) , mathematics , algorithm , artificial intelligence , machine learning , statistics , physics , geometry , quantum mechanics , biology , probabilistic logic , genetics , programming language , operating system
In this work, we consider robust predictive control of switched uncertain nonlinear systems required to satisfy a prescribed switching sequence with uncertainty in the switching times subject to state and input constraints. To illustrate our approach, we consider first the problem of satisfying a prescribed schedule subject to uncertainty only in the switching times. Predictive controllers that guarantee the satisfication of state and input constraints from an explicitly characterized set ofinitial conditions are first designed. The performance and constraint‐handling capabilities of the predictive controllers are subsequently utilized in ensuring the satisfaction of the switching schedule while preserving stability. The results are then generalized to address the problem in the presence of parametric uncertainty and exogenous time‐varying disturbances in the dynamics of the constituent modes. The proposed control method is demonstrated through application to a scheduled chemical process example. Copyright © 2007 John Wiley & Sons, Ltd.