Model predictive control (MPC) is capable to deal with multiconstraint systems in real control
processes; however, the heavy computation makes it difficult to implement. In this paper, a …

Die effiziente Lösung von Optimierungsproblemen in Echtzeit bildet die Grundlage vieler
moderner Regelungs-und Schätzverfahren. So basieren die prädiktive Regelung sowie die …

This paper studies a linear matrix inequality (LMI)‐based robust event‐triggered model
predictive control (ET‐MPC) for a class of discrete linear time‐invariant systems subject to …

We implement a recently proposed event-triggered networked model predictive control
(MPC) approach on industrial hardware to analyze its practical relevance. There exist …

An event‐triggered robust model predictive control (MPC) approach is proposed for linear
discrete‐time systems with bounded disturbances. According to the probability distribution of …

The optimal solution to a linear model predictive control (MPC) problem is usually
understood as the optimal input for the current state, ie, a point in state space. However, the …

Recently, a regional MPC approach has been proposed that exploits the piecewise affine
structure of the optimal solution (without computing the entire explicit solution before). Here …

We propose a method for determining fallback control laws for nonlinear MPC problems. A
fallback strategy is needed whenever a nonlinear MPC problem cannot be solved in due …

We extend a recently proposed robust event-triggered MPC approach that exploits the
piecewise affine structure of the solution. Robust optimal feedback laws and their regions of …

We show how to exploit the piecewise affine structure of the optimal control law in networked
linear-quadratic MPC. The complete explicit solution is not required in this approach, but the …