We propose a reference-free learning model predictive controller for periodic repetitive tasks. We consider a problem in which dynamics, constraints and stage cost are periodically time-varying. The controller uses the closed-loop data to construct a time-varying terminal set and a time-varying terminal cost. We show that the proposed strategy in closed loop with linear and nonlinear systems guarantees recursive constraints satisfaction, non-increasing open-loop cost, and that the open-loop and closed-loop cost are the same at convergence. Simulations are presented for different repetitive tasks, both for linear and nonlinear systems.

Learning model predictive control for periodic repetitive tasks / Scianca, Nicola; Rosolia, Ugo; Borrelli, Francesco. - (2020), pp. 29-34. (Intervento presentato al convegno 2020 European Control Conference (ECC) tenutosi a St. Petersburg; Russia).

Learning model predictive control for periodic repetitive tasks

Nicola Scianca
Primo
;
2020

Abstract

We propose a reference-free learning model predictive controller for periodic repetitive tasks. We consider a problem in which dynamics, constraints and stage cost are periodically time-varying. The controller uses the closed-loop data to construct a time-varying terminal set and a time-varying terminal cost. We show that the proposed strategy in closed loop with linear and nonlinear systems guarantees recursive constraints satisfaction, non-increasing open-loop cost, and that the open-loop and closed-loop cost are the same at convergence. Simulations are presented for different repetitive tasks, both for linear and nonlinear systems.
2020
2020 European Control Conference (ECC)
model predictive control; periodic systems; nonlinear systems;
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Learning model predictive control for periodic repetitive tasks / Scianca, Nicola; Rosolia, Ugo; Borrelli, Francesco. - (2020), pp. 29-34. (Intervento presentato al convegno 2020 European Control Conference (ECC) tenutosi a St. Petersburg; Russia).
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Note: DOI: 10.23919/ECC51009.2020.9143857
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1522267
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