4 citations · 9 across the 10 of their papers we have counts for
12 papers
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…
Derivative-Free Data-Driven Control of Continuous-Time Linear Time-Invariant Systems
Alessandro Bosso, Marco Borghesi, Andrea Iannelli +2
This paper develops a data-driven stabilization method for continuous-time linear time-invariant systems with theoretical guarantees and no need for signal derivatives. The framewo…
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…
A hybrid systems framework for data-based adaptive control of linear time-varying systems
Andrea Iannelli, Romain Postoyan
We consider the data-driven stabilization of discrete-time linear time-varying systems. The controller is defined as a linear state-feedback law whose gain is adapted to the plant…
On the Regret of Recursive Methods for Discrete-Time Adaptive Control with Matched Uncertainty
Aren Karapetyan, Efe C. Balta, Anastasios Tsiamis +2
Continuous-time adaptive controllers for systems with a matched uncertainty often comprise an online parameter estimator and a corresponding parameterized controller to cancel the…
Learning Soft Constrained MPC Value Functions: Efficient MPC Design and Implementation providing Stability and Safety Guarantees
Nicolas Chatzikiriakos, Kim P. Wabersich, Felix Berkel +2
Model Predictive Control (MPC) can be applied to safety-critical control problems, providing closed-loop safety and performance guarantees. Implementation of MPC controllers requir…
Closed-Loop Finite-Time Analysis of Suboptimal Online Control
Aren Karapetyan, Efe C. Balta, Andrea Iannelli +1
Suboptimal methods in optimal control arise due to a limited computational budget, unknown system dynamics, or a short prediction window among other reasons. Although these methods…
A harmonic framework for the identification of linear time-periodic systems
Flora Vernerey, Pierre Riedinger, Andrea Iannelli +1
This paper presents a novel approach for the identification of linear time-periodic (LTP) systems in continuous time. This method is based on harmonic modeling and consists in conv…