4 citations · 9 across the 10 of their papers we have counts for
11 papers · 1 filter
A Stochastic Gradient Descent Approach to Design Policy Gradient Methods for LQR
Bowen Song, Simon Weissmann, Mathias Staudigl +1
In this work, we propose a stochastic gradient descent (SGD) framework to design data-driven policy gradient descent algorithms for the linear quadratic regulator problem. Two alte…
Data-Driven Stabilization of Continuous-Time LTI Systems from Noisy Input-Output Data
Alessandro Bosso, Marco Borghesi, Andrea Iannelli +2
We present an approach to compute stabilizing controllers for continuous-time linear time-invariant systems directly from an input-output trajectory affected by process and measure…
High Effort, Low Gain: Fundamental Limits of Active Learning for Linear Dynamical Systems
Nicolas Chatzikiriakos, Kevin Jamieson, Andrea Iannelli
In this work, we consider the problem of identifying an unknown linear dynamical system given a finite hypothesis class. In particular, we analyze the effect of the excitation inpu…
Data-Driven Control of Continuous-Time LTI Systems via Non-Minimal Realizations
Alessandro Bosso, Marco Borghesi, Andrea Iannelli +2
This article proposes an approach to design output-feedback controllers for unknown continuous-time linear time-invariant systems using only input-output data from a single experim…
End-to-end guarantees for indirect data-driven control of bilinear systems with finite stochastic data
Nicolas Chatzikiriakos, Robin Strässer, Frank Allgöwer +1
In this paper we propose an end-to-end algorithm for indirect data-driven control for bilinear systems with stability guarantees. We consider the case where the collected i.i.d. da…
Sample Complexity Bounds for Linear System Identification from a Finite Set
Nicolas Chatzikiriakos, Andrea Iannelli
This paper considers a finite sample perspective on the problem of identifying an LTI system from a finite set of possible systems using trajectory data. To this end, we use the ma…