Predictive control for polytopic uncertain linear systems with guaranteed constraints satisfaction
SHENG Yun-long
SU Hong-ye
CHU Jian
Abstract：Based on the invariant set theory, invariance constraint predictive control (IC-PC) first proposed by Chiscil et al, is extended and generalized to a framework of model predictive control for constrained linear systems with polytopic uncertainty. The crucial point is to reformulate online optimization problem corresponding to nominal model with an appropriate additional robust and feasible constraint. It is shown that in this configuration feasibility of online optimization problem as well as satisfaction of constraints for the real plant can be guaranteed in all time steps if the optimization problem is feasible at the initial stage. Moreover, a sufficient condition of robust stability is given for closed-loop uncertain system, which provides a guide to the choice of cost function to guarantee robust stability.
Keywords：predictive controlinvariant setconstrained systemspolytopic uncertainty
Publication Date：2003-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 193-198 )