Many authors have noted the difficulty of developing the models required for nonlinear
model predictive control (NMPC) and other nonlinear, model-based control strategies. One …

This monograph systematically presents the existing identification methods of nonlinear
systems using the block-oriented approach It surveys various known approaches to the …

Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-
chemical reactions, where multiphases and multifields interactions with long time delay …

Modern Predictive Control explains how MPC differs from other control methods in its
implementation of a control action. Most importantly, MPC provides the flexibility to act while …

This research monograph summarizes solutions to reconfigurable fault-tolerant control
problems for nonlinear dynamical systems that are based on the fault-hiding principle. It …

The benefits of using the Wiener model based identification and control methodology
presented in this paper, compared to linear techniques, are demonstrated for dual …

This paper considers the modeling and control problem for nonstationary nonlinear systems
whose dynamic characteristics depend on time-varying working-points and may be locally …

Among the multitude of modern control methods, model predictive control (MPC) is one of
the most successful–. As noted in “Summary,” this success is largely due to the ability of …

It poses significant challenge to control Hammerstein–Wiener systems involving modeling
nonlinearities. In this paper, a novel data-driven predictive control method based on the …

Economic model predictive control (EMPC) is a feedback control technique that attempts to
tightly integrate economic optimization and feedback control since it is a predictive control …