230 citations · 372 across the 23 of their papers we have counts for
6 papers · 1 filter
Data-Driven Robust MPC for Unknown Nonlinear Systems via Set-Membership Learning
Yuzhou Wei, Wenjie Liu, Yifan Xie +3
Data-driven model predictive control (MPC) has become an attractive approach for controlling unknown systems, especially when data are corrupted by noise. However, most existing da…
On stability and non-averaged performance of economic MPC with terminal conditions for optimal periodic operation
Jonas Mair, Lukas Schwenkel, Matthias A. Müller +1
Operation at steady state is often not optimal when optimizing over an economic cost objective. In many cases, periodic operation yields better performance. Therefore, we derive as…
Discrete-Time Event-Triggered Extremum Seeking
Victor Hugo Pereira Rodrigues, Tiago Roux Oliveira, Miroslav Krstić +1
This paper proposes a discrete-time event-triggered extremum seeking control scheme for real-time optimization of nonlinear systems. Unlike conventional discrete-time implementatio…
Robust IMMPC: An Offset-free MPC for Rejecting Unknown Disturbances
Felix Brändle, Frank Allgöwer
Output regulation is the problem of finding a control input to asymptotically track reference trajectories and reject disturbances. This can be addressed by using the internal mode…
Adaptive Data-Driven Min-Max MPC for Linear Time-Varying Systems
Yifan Xie, Julian Berberich, Frank Allgöwer
In this paper, we propose an adaptive data-driven min-max model predictive control (MPC) scheme for discrete-time linear time-varying (LTV) systems. We assume that prior knowledge…
Safety for Weakly-Hard Control Systems via Graph-Based Barrier Functions
Marc Seidel, Mahathi Anand, Frank Allgöwer
Despite significant advancement in technology, communication and computational failures are still prevalent in safety-critical engineering applications. Often, networked control sy…