Recurrent Equilibrium Network Models for Nonlinear Model Predictive Control

In this paper the design of a nonlinear Model Predictive Control algorithm based on Recurrent Equilibrium Network models is addressed. Firstly, a tailored observer for the Recurrent Equilibrium Network model is proposed, in order to provide to the Model Predictive Control optimization an initialization that takes into account the past history of the system. Then, the Model Predictive Control optimization is designed including a proper terminal cost to guarantee closed loop stability for any choice of the prediction horizon. Copyright (C) 2024 The Authors.