Neural network‐based offset‐free model predictive control for nonlinear systems

Abstract This paper proposes an offset‐free model predictive control (MPC) framework for nonlinear systems modeled using neural network‐based nonlinear autoregressive models with exogenous inputs (NARX). To address plant‐model mismatch and ensure offset‐free tracking, the NARX model is augmented with an integrating disturbance model, resulting in an extended state‐space suitable for MPC. A nonlinear observer is developed to estimate both system …