We investigate adaptive strategies to robustly and optimally control the COVID-19 pandemic
via social distancing measures based on the example of Germany. Our goal is to minimize …

Min-max model predictive control (MPC) is one of the few techniques suitable for robust
stabilization of uncertain nonlinear systems subject to constraints. Stability issues as well as …

In this article, we present a nonlinear robust model predictive control (MPC) framework for
general (state and input dependent) disturbances. This approach uses an online …

This paper extends tube‐based model predictive control of linear systems to achieve robust
control of nonlinear systems subject to additive disturbances. A central or reference …

This paper deals with the robustness of Model Predictive Controllers for constrained
uncertain nonlinear systems. The uncertainty is assumed to be modeled by a state and input …

In the Proportional-Integral-Derivative (PID) controllers the control signal is a linear function
of: the current control error (the proportional part), the past errors (the integral part) and the …

In this paper, a method is proposed for the adaptive model predictive control of constrained
nonlinear system. Rather than relying on the inherent robustness properties of standard …

Model Predictive Control (MPC) is an area in rapid development with respect to both
theoretical and application aspects. The former petrochemical applications of MPC were …

The past three decades have seen rapid development in the area of model predictive control
with respect to both theoretical and application aspects. Over these 30 years, model …

In this article, we present a tube‐based framework for robust adaptive model predictive
control (RAMPC) for nonlinear systems subject to parametric uncertainty and additive …