A common feature ofmany practical control problems is the presence of constraints.
Predictive control methods such as generalised predictive control (GPC) are suitable for …

A difficulty with constrained nonlinear control is the minimization of the cost function. With
complex system representations such as fundamental models, the required optimization …

This paper shows how to improve the robustness of mobile robot path tracking when
predictive control algorithms are used. When uncertainties in a mobile robot are considered …

This paper deals with the application of a model predictive controller (MPC) for tracking to a
real system: a linear motor. The MPC formulation used in this paper in a novel approach to …

In this paper we present a new technique to face the so-called constrained Model Predictive
Control. The main advantage of this new approach with respect to other well-known …

This note studies the formulation of model predictive control exploiting passivity properties.
The introduction of passive constraints in model predictive control schemes is particularly …

A new design technique for a robust model predictive controller is proposed using an
uncertainty description expressed in the time-domain. Robust stability of the resulting closed …

In this paper, a general framework for trajectory planning for specified tasks in a dynamic
environment is discussed. Since we are interested in dynamic tasks and environments, a" …

The paper suggests a new approach to navigation of mobile robots, based on nonlinear
model predictive control and using a navigation function as a control Lyapunov function. In …

In this paper the Model Predictive Control (MPC) strategy is used to solve the mobile robot
trajectory tracking problem, where controller must ensure that robot follows pre-calculated …