Robust offset‐free nonlinear model predictive control for systems learned by neural nonlinear autoregressive exogenous models

Abstract

AbstractThis paper presents a robust model predictive control (MPC) scheme that provides offset‐free setpoint tracking for systems described by neural nonlinear autoregressive exogenous (NNARX) models. To this end, a NNARX model that learns the dynamics of the plant from input‐output data is augmented with an explicit integral action on the output tracking error. A robust tube‐based MPC is finally designed, leveraging the unique structure of the model, to ensure robust offset‐free convergence to constant reference signals even in case of plant‐model mismatch. Numerical simulations on a water heating system show the effectiveness of the proposed control algorithm.