10 papers
Fundamental Limitations of Data-Driven Control: A Statistical Decision Perspective
Jiabao He, Feiran Zhao, Yushan Li +3
Substantial research efforts have been devoted to the design of data-driven controllers; however, comparatively less is known about their statistical performance and fundamental li…
Adaptive Control of Unknown Linear Switched Systems via Policy Gradient Methods
Felix Laurent, Feiran Zhao, Jaap Eising +1
We consider the policy gradient adaptive control (PGAC) framework, which adaptively updates a control policy in real time, by performing data-based gradient descent steps on the li…
Convergence and Robustness Bounds for Distributed Asynchronous Shortest-Path
Jared Miller, Mattia Bianchi, Florian Dörfler
This work analyzes convergence times and robustness bounds for asynchronous distributed shortest-path computation. We focus on the Adaptive Bellman--Ford algorithm, a self-stabiliz…
The Bias of Subspace-based Data-Driven Predictive Control
Keith Moffat, Florian Dörfler, Alessandro Chiuso
This paper quantifies and addresses the bias of subspace-based Data-Driven Predictive Control (DDPC) for linear, time-invariant (LTI) systems. The primary focus is the bias that ar…
Grid-Connected, Data-Driven Inverter Control, Theory to Hardware
Sebastian Graf, Keith Moffat, Anurag Mohapatra +2
Grid-connected inverter control is challenging to implement due to the difficulty of obtaining and maintaining an accurate grid model. Direct Data-Driven Predictive Control provide…
Recursive-ARX for Grid-Edge Fault Detection
Soufiane El Yaagoubi, Keith Moffat, Eduardo Prieto Araujo +1
Future electrical grids will require new ways to identify faults as inverters are not capable of supplying large fault currents to support existing fault detection methods and beca…