Input-to-state stable MPC for constrained discrete-time nonlinear systems with bounded additive uncertainties

In this paper a robust model predictive control (MPC) for constrained discrete-time nonlinear system with additive uncertainties is presented. This controller uses a terminal cost, terminal constraint and nominal predictions. The terminal region and constraints on the states are computed to get robu...

Full description

Saved in:
Bibliographic Details
Published inProceedings of the 41st IEEE Conference on Decision and Control, 2002 Vol. 4; pp. 4619 - 4624 vol.4
Main Authors Marruedo, D.L., Alamo, T., Camacho, E.F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2002
Subjects
Additives
Automatic control
Closed loop systems
Control systems
Costs
Nonlinear systems
Robustness
Stability analysis
Telephony
Uncertainty
Online AccessGet full text
ISBN0780375165
9780780375161
ISSN0191-2216
DOI10.1109/CDC.2002.1185106

Cover

More Information
Summary:In this paper a robust model predictive control (MPC) for constrained discrete-time nonlinear system with additive uncertainties is presented. This controller uses a terminal cost, terminal constraint and nominal predictions. The terminal region and constraints on the states are computed to get robust feasibility of the closed loop system for a given bound on the admissible uncertainties. Furthermore, it is proved that the closed-loop system is input-to-state stable with relation to the uncertainties. Therefore, the closed-loop system evolves towards a compact set where it is ultimately bounded. In case of decaying uncertainties, the closed-loop system is asymptotically stable. The convergence of the closed loop system is guaranteed despite the suboptimality of the solution.
ISBN:0780375165
9780780375161
ISSN:0191-2216
DOI:10.1109/CDC.2002.1185106