3 citations · 3 across the 7 of their papers we have counts for
7 papers · 1 filter
On Tikhonov Regularization for Direct and Indirect Data-Driven LQR Control
Shuyuan Zhang, Zheming Wang, Raphael M. Jungers
In recent years, the so-called `direct data-driven control' has been a topic of intense research, and it is expected that it will become prominent in future complex dynamical syste…
Random Reshuffling-Based Distributed Nash Equilibrium Seeking
Jun Hu, Chao Sun, Chen Bo +2
This paper studies random reshuffling (RR)-based distributed Nash equilibrium seeking for noncooperative games. The game is motivated as a sample-average approximation of an underl…
Data-driven invariant subspace identification for black-box switched linear systems
Guillaume O. Berger, Raphaël M. Jungers, Zheming Wang
We present an algorithmic framework for the identification of candidate invariant subspaces for switched linear systems. Namely, the framework allows to compute an orthonormal basi…
Probabilistic guarantees on the objective value for the scenario approach via sensitivity analysis
Zheming Wang, Raphaël M. Jungers
This paper is concerned with objective value performance of the scenario approach for robust convex optimization. A novel method is proposed to derive probabilistic bounds for the…
Data-driven stability analysis of switched linear systems with Sum of Squares guarantees
Anne Rubbens, Zheming Wang, Raphaël M. Jungers
We present a new data-driven method to provide probabilistic stability guarantees for black-box switched linear systems. By sampling a finite number of observations of trajectories…
Chance-constrained quasi-convex optimization with application to data-driven switched systems control
Guillaume O. Berger, Raphaël M. Jungers, Zheming Wang
We study quasi-convex optimization problems, where only a subset of the constraints can be sampled, and yet one would like a probabilistic guarantee on the obtained solution with r…