Abstract Model predictive control (MPC) has achieved considerable success in the process
industries, with its ability to deal with linear and nonlinear models, while observing system …

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 …

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 …

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

Hydroelectric power stations are a major source of electricity around the world;
understanding their dynamics is crucial to achieving good performance. The electrical power …

The book presents a significant expansion in depth and breadth of the previous edition. It
includes substantially more numerical illustrations and copious supporting MATLAB code …

The series Advances in Industrial Control aims to report and encourage technology transfer
in control engineering. The rapid development of control technology has an impact on all …

Progress in the design and use of Model-Based Predictive Control is reviewed. The two-
degree-of-freedom solution of many predictive algorithms enables optimal set-point …

Reliable control of superheated steam temperature is necessary to ensure high efficiency
and high load-following capability in the operation of modern power plant. This is often …