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Robust constrained nonlinear Model Predictive Control with Gated Recurrent Unit model -- Extended version
Published 19 Jul 2023 in eess.SY and cs.SY | (2307.10069v3)
Abstract: In this paper we propose a robust Model Predictive Control where a Gated Recurrent Unit network model is used to learn the input-output dynamic of the system under control. Robust satisfaction of input and output constraints and recursive feasibility in presence of model uncertainties are achieved using a constraint tightening approach. Moreover, new terminal cost and terminal set are introduced in the Model Predictive Control formulation to guarantee Input-to-State Stability of the closed loop system with respect to the uncertainty term.
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