This paper presents a tube-based robust economic MPC controller for discrete-time nonlinear systems that are perturbed by disturbance inputs. The proposed algorithm minimizes a modified economic objective function which considers the worst cost within a tube around the solution of the associated nominal system. Recursive feasibility and an a-priori upper bound to the closed-loop asymptotic average performance are ensured. Thanks to the use of dissipativity of the nominal system with a suitable supply rate, the closed-loop system under the proposed controller is shown to be asymptotically stable, in the sense that it is driven to an optimal robust invariant set. Finally, some illustrative examples, optimally operated at qualitatively different regimes, are addressed and the performances by using our new controller and those in the literature are compared.

Tube-based robust Economic Model Predictive Control on dissipative systems with generalized optimal regimes of operation / Dong, Zihang; Angeli, David. - ELETTRONICO. - (2018), pp. 4309-4314. ( IEEE Conference on Decision and Control).

Tube-based robust Economic Model Predictive Control on dissipative systems with generalized optimal regimes of operation

Angeli, David
2018

Abstract

This paper presents a tube-based robust economic MPC controller for discrete-time nonlinear systems that are perturbed by disturbance inputs. The proposed algorithm minimizes a modified economic objective function which considers the worst cost within a tube around the solution of the associated nominal system. Recursive feasibility and an a-priori upper bound to the closed-loop asymptotic average performance are ensured. Thanks to the use of dissipativity of the nominal system with a suitable supply rate, the closed-loop system under the proposed controller is shown to be asymptotically stable, in the sense that it is driven to an optimal robust invariant set. Finally, some illustrative examples, optimally operated at qualitatively different regimes, are addressed and the performances by using our new controller and those in the literature are compared.
2018
2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC)
IEEE Conference on Decision and Control
Dong, Zihang; Angeli, David
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1153400
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