Nonlinear Predictive Control Using Wiener Models - Computationally Efficient Approaches for Polynomial and Neural Structures

The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to cancel the influence of process nonlinearity. Unfortunately, the model's structure is limited, and it gives poor control quality in the case of an imperfect model and disturbances.