… In Chapter 5, multivariable constrained predictive control algorithms are presented with
DMC as an illustration example, focusing on the description of online optimization and the …

… The predictive capability is obtained by embedding a mathematical model of the system’s
dynamics as constraints in the optimization, and additional state and control constraints can …

… in industrial plants Multivariable Predictive Control: … multivariate predictive control (MPC)
applications, as well as expert guidance on how to derive maximum benefit from those systems. …

… iterative learning model predictive control (LV-ILMPC) method is presented for trajectory
tracking in batch processes. Different from the iterative learning model predictive control (ILMPC…

… handle the multivariable case, system constraint, and non-linearities in a very simple way. …
This paper proposes a model predictive control for the pan and tilt angle of the 2-DOF robotics …

… Inspired by the above works, this work presents a model predictive control strategy for robot
… • To improve the servo efficiency and control accuracy of constrained IBVS systems, this …

… tion problem with a constraint on the steadystate response of the system. For linear, timeinvariant,
systems the problem can be solved provided a system of linear matrix equations …

… This study investigates the problem of robust model predictive control (RMPC) for active
suspension systems with time-varying delays and input constraints. The uncertainty is of convex …

… Robotic systems are mechanical systems with actuators to … control of nonlinear processes
subjected to constraints on the … In this paper, a nonlinear predictive control approach is …

… The classes of constrained linear systems and linear hybrid systems treated in this book
cover many, if not most, practical problems. The new design techniques hold the promise to lead …