This paper discusses a nonlinear Model Predictive Control (MPC) algorithm for multiple-
input multiple-output dynamic systems represented by cascade Hammerstein–Wiener …

This paper is concerned with computationally efficient nonlinear model predictive control
(MPC) of dynamic systems described by cascade Wiener–Hammerstein models. The Wiener …

This work is concerned with state space Multiple-Input Multiple-Output (MIMO) Wiener
systems which consist of a linear dynamic block connected in series with a nonlinear steady …

In this paper a model-based predictive control (MPC) algorithm is presented for
Hammerstein? Wiener systems. This type of system consists of a linear dynamic block …

Block-structured models, such as Wiener or Hammerstein models, have been used in
nonlinear model predictive control to reduce the cost of identification and online …

A nonlinear generalized predictive control algorithm based upon a Hammerstein model is
presented. Stability of the closed-loop system is analyzed with a control horizon equal to …

This paper develops a nonlinear model predictive control (MPC) algorithm for dynamic
systems represented by piecewise linear (PWL) Hammerstein models. At each sampling …

Wiener systems are characterized by a linear dynamic block followed by a static
nonlinearity. In the paper a model-based predictive control (MPC) strategy is proposed for …

In the process industry, there exist many systems which can be approximated by a
Hammerstein model. Moreover, these systems are usually subjected to input magnitude …

This paper addresses synthesis approaches to output feedback model predictive control
(OFMPC) for systems with Hammerstein–Wiener nonlinearity and bounded …