In the design of predictive controllers (MPC), parameterisation of degrees of freedom by
Laguerre functions, has shown to improve the controller performance and feasible region …

Abstract Model predictive control (MPC) is one of the most used optimization-based control
strategies for large-scale systems, since this strategy allows to consider a large number of …

Model Predictive Control is a valuable tool for the process control engineer in a wide variety
of applications. Because of this the structure of an MPC can vary dramatically from …

A tuning procedure for a model predictive controller (MPC) is presented for multi-input multi-
output systems. The approach consists of two steps based on a hybrid method: the goal …

This paper develops the recently published Laguerre MPC by proposing an alternative
parametrization of the degrees of freedom in order to further increase the feasible region of …

In model-predictive control (MPC), achieving the best closed-loop performance under a
given computational capacity is the underlying design consideration. This paper analyzes …

The ability to take constraints explicitly into account in the optimisation problem formulation
has made Model Predictive Control (MPC) a popular control strategy. However, finding the …

Predictive control has received much attention from both theoreticians and practitioners in
diverse fields. However, a challenging problem we must face is how to auto-tune the …

Generalized predictive control algorithms are a powerful control design method widely
applied to industrial processes. However, there is no easy way to tune the design …

This paper makes contributions in the area of predictive control and in particular examines to
what extent different methods for parameterising the degrees of freedom within the input …