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20192022
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eess.SY2022

A novel constraint tightening approach for robust data-driven predictive control

Christian Klöppelt, Julian Berberich, Frank Allgöwer +1

In this paper, we present a data-driven model predictive control (MPC) scheme that is capable of stabilizing unknown linear time-invariant systems under the influence of process di…

eess.SY2021

Robust output feedback model predictive control using online estimation bounds

Johannes Köhler, Matthias A. Müller, Frank Allgöwer

We present a framework to design nonlinear robust output feedback model predictive control (MPC) schemes that ensure constraint satisfaction under noisy output measurements and dis…

eess.SY2021

Data-Based System Analysis and Control of Flat Nonlinear Systems

Mohammad Alsalti, Julian Berberich, Victor G. Lopez +2

Willems et al. showed that all input-output trajectories of a discrete-time linear time-invariant system can be obtained using linear combinations of time shifts of a single, persi…

eess.SY2020

Robust Stability of Suboptimal Moving Horizon Estimation using an Observer-Based Candidate Solution

Julian D. Schiller, Sven Knüfer, Matthias A. Müller

In this paper, we propose a suboptimal moving horizon estimator for nonlinear systems. For the stability analysis we transfer the "feasibility-implies-stability/robustness" paradig…

eess.SY2020

Periodic optimal control of nonlinear constrained systems using economic model predictive control

Johannes Köhler, Matthias A. Müller, Frank Allgöwer

In this paper, we consider the problem of periodic optimal control of nonlinear systems subject to online changing and periodically time-varying economic performance measures using…

eess.SY2020

Robust Constraint Satisfaction in Data-Driven MPC

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

We propose a purely data-driven model predictive control (MPC) scheme to control unknown linear time-invariant systems with guarantees on stability and constraint satisfaction in t…