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Robust Model Predictive Control of Nonlinear Systems With Bounded and State-Dependent Uncertainties

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4 Author(s)
Pin, G. ; Dept. of Electr., Electron. & Comput. Eng., Univ. of Trieste, Trieste, Italy ; Raimondo, D.M. ; Magni, L. ; Parisini, T.

In this note, a robust model predictive control scheme for constrained discrete-time nonlinear systems affected by bounded disturbances and state-dependent uncertainties is presented. In order to guarantee the robust satisfaction of the state constraints, restricted constraint sets are introduced in the optimization problem, by exploiting the state-dependent nature of the considered class of uncertainties. Moreover, unlike the nominal model predictive control algorithm, a stabilizing state constraint is imposed at the end of the control horizon in place of the usual terminal constraint posed at the end of the prediction horizon. The regional input-to-state stability of the closed-loop system is analyzed. A simulation example shows the effectiveness of the proposed approach.

Published in:

Automatic Control, IEEE Transactions on  (Volume:54 ,  Issue: 7 )

Date of Publication:

July 2009

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