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eess.SY2019

Dissipativity in economic model predictive control: beyond steady-state optimality

Matthias A. Müller

This chapter provides a concise survey on different dissipativity conditions that have appeared in the literature on economic model predictive control and discusses their decisive…

eess.SY2019

A nonlinear tracking model predictive control scheme for dynamic target signals

Johannes Köhler, Matthias A. Müller, Frank Allgöwer

We present a nonlinear model predictive control (MPC) scheme for tracking of dynamic target signals. The scheme combines stabilization and dynamic trajectory planning in one layer,…

eess.SY2019

A robust adaptive model predictive control framework for nonlinear uncertain systems

Johannes Köhler, Peter Kötting, Raffaele Soloperto +2

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

eess.SY2019

A computationally efficient robust model predictive control framework for uncertain nonlinear systems -- extended version

Johannes Köhler, Raffaele Soloperto, Matthias A. Müller +1

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

eess.SY2019

Data-Driven Tracking MPC for Changing Setpoints

Julian Berberich, Johannes Köhler, Matthias A. Müller +1

We propose a data-driven tracking model predictive control (MPC) scheme to control unknown discrete-time linear time-invariant systems. The scheme uses a purely data-driven system…

eess.SY2019

Linear robust adaptive model predictive control: Computational complexity and conservatism -- extended version

Johannes Köhler, Elisa Andina, Raffaele Soloperto +2

In this paper, we present a robust adaptive model predictive control (MPC) scheme for linear systems subject to parametric uncertainty and additive disturbances. The proposed appro…