Model Predictive Control System Design and Implementation Using MATLAB® proposes
methods for design and implementation of MPC systems using basis functions that confer …

The control problem was formulated in the previous chapters considering all signals to
possess an unlimited range. This is not very realistic because in practice all processes are …

The formulation and final control law of two of the more popular MPC algorithms, dynamic
matrix control (DMC) and generalised predictive controller (GPC), are specially analysed in …

Receding Horizon Control introduces the essentials of a successful feedback strategy that
has emerged in many industrial fields: the process industries in particular. Receding horizon …

This paper addresses predictive state regulation of linear discrete-time systems subject to
persistent bounded disturbances and to state and/or control constraints. It is well known that …

Predictive constrained control of time-varying and/or uncertain linear systems has been
effected through the use of ellipsoidal invariant sets (Kothare et al., 1996). Linear matrix …

The series Advances in Industrial Control aims to report and encourage technology transfer
in control engineering. The rapid development of control technology impacts all areas of the …

Control and automation in its broadest sense plays a fundamental role in process industries.
Control assures stability of technologies, disturbance attenuation, safety of equipment and …

In this paper we introduce a new stage cost and show that the use of this cost allows one to
formulate a robustly stable feedback min–max model predictive control problem that can be …

Recent work with predictive control strategies has shown that the stable GPC (SGPC)
approach has significant computational and numerical advantages. However, SGPC is cast …