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A predictive control strategy for norm‐bounded LPV discrete‐time systems with bounded rates of parameter change
Author(s) -
Casavola Alessandro,
Famularo Domenico,
Franzè Giuseppe
Publication year - 2007
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.1260
Subject(s) - bounded function , control theory (sociology) , model predictive control , norm (philosophy) , mathematics , upper and lower bounds , discrete time and continuous time , quadratic equation , constraint (computer aided design) , invariant (physics) , mathematical optimization , time horizon , computer science , control (management) , mathematical analysis , statistics , geometry , artificial intelligence , political science , law , mathematical physics
A novel predictive control strategy for input‐saturated norm‐bounded linear parameter varying discrete‐time systems is proposed. The solution is computed by minimizing an upper bound to the ‘worst‐case’ infinite horizon quadratic cost under the constraint of steering the future state evolutions, emanating from the current state, into a feasible and positive invariant set. It will be shown that the ‘size’ of this terminal set depends on the rate of change of the scheduling parameter, which is assumed to be bounded and measurable. Copyright © 2007 John Wiley & Sons, Ltd.