Model predictive control design for dynamical systems learned by Long Short-Term Memory Networks

27 Aug 2020 • Terzi Enrico • Bonassi Fabio • Farina Marcello • Scattolini Riccardo

This paper analyzes the stability-related properties of Long Short-Term Memory (LSTM) networks and investigates their use as the model of the plant in the design of Model Predictive Controllers (MPC). First, sufficient conditions guaranteeing the Input-to-State stability (ISS) and Incremental Input-to-State stability (dISS) of LSTM are derived... (read more)

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Model predictive control design for dynamical systems learned by Long Short-Term Memory Networks

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