Robust Model Predictive Control of continuous-time sampled-data nonlinear systems with Integral Sliding Mode

Author

Rubagotti, M. ; Raimondo, D.M. ; Ferrara, A. ; Magni, L.

Author_Institution

Dept. of Comput. Eng. & Syst. Sci., Univ. of Pavia, Pavia, Italy

fYear

2009

fDate

23-26 Aug. 2009

Firstpage

2247

Lastpage

2252

Abstract

A hierarchical Nonlinear Model Predictive Control (NMPC) scheme with guaranteed Input-to-State-practical-Stability (ISpS) is proposed. The controller is formed by an Integral Sliding Mode (ISM) controller and a NMPC one. The ISM, relying on the knowledge of the nominal continuous-time model of the system and of the piecewise constant control signal generated by the NMPC produces a control action aimed at reducing the difference between the dynamics of the nominal closed-loop system and the actual evolution of the state. The NMPC in this way can be designed based on a system with reduced uncertainty. In order to prove the stability of the overall control scheme, some general Regional ISpS results for continuous-time systems are proven.

Keywords

closed loop systems; continuous time systems; control system synthesis; hierarchical systems; nonlinear control systems; piecewise constant techniques; predictive control; robust control; sampled data systems; uncertain systems; variable structure systems; ISM controller; NMPC scheme; closed-loop system; continuous-time sampled-data nonlinear systems; control action; general regional ISpS; hierarchical nonlinear model predictive control scheme; input-to-state-practical-stability; integral sliding mode; nominal continuous-time model; piecewise constant control signal; reduced uncertainty; robust control; Closed loop systems; Economic indicators; Manifolds; Predictive control; Robustness; Stability analysis; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (ECC), 2009 European

Conference_Location

Budapest

Print_ISBN

978-3-9524173-9-3

Type

conf

Filename

7074739