28 citations · 55 across the 18 of their papers we have counts for
19 papers
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…
Learning stability guarantees for constrained switching linear systems from noisy observations
Adrien Banse, Zheming Wang, Raphaël M. Jungers
We present a data-driven framework based on Lyapunov theory to provide stability guarantees for a family of hybrid systems. In particular, we are interested in the asymptotic stabi…
Learning stability of partially observed switched linear systems
Zheming Wang, Raphaël M. Jungers, Mihály Petreczky +2
This paper deals with learning stability of partially observed switched linear systems under arbitrary switching. Such systems are widely used to describe cyber-physical systems wh…
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…
Black-box stability analysis of hybrid systems with sample-based multiple Lyapunov functions
Adrien Banse, Zheming Wang, Raphaël M. Jungers
We present a framework based on multiple Lyapunov functions to find probabilistic data-driven guarantees on the stability of unknown constrained switching linear systems (CSLS), wh…
Learning stability guarantees for data-driven constrained switching linear systems
Adrien Banse, Zheming Wang, Raphaël M. Jungers
We consider stability analysis of constrained switching linear systems in which the dynamics is unknown and whose switching signal is constrained by an automaton. We propose a data…
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 affine systems
Matteo Della Rossa, Zheming Wang, Lucas N. Egidio +1
We consider discrete-time switching systems composed of a finite family of affine sub-dynamics. First, we recall existing results and present further analysis on the stability prob…
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…
Data-driven control of switched linear systems with probabilistic stability guarantees
Zheming Wang, Guillaume O. Berger, Raphaël M. Jungers
This paper tackles state feedback control of switched linear systems under arbitrary switching. We propose a data-driven control framework that allows to compute a stabilizing stat…
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…
Immersion-based model predictive control of constrained nonlinear systems: Polyflow approximation
Zheming Wang, Raphaël M. Jungers
In the framework of Model Predictive Control (MPC), the control input is typically computed by solving optimization problems repeatedly online. For general nonlinear systems, the o…
Computation of invariant sets via immersion for discrete-time nonlinear systems
Zheming Wang, Raphaël M. Jungers, Chong-Jin Ong
In this paper, we propose an approach for computing invariant sets of discrete-time nonlinear systems by lifting the nonlinear dynamics into a higher dimensional linear model. In p…
A data-driven method for computing polyhedral invariant sets of black-box switched linear systems
Zheming Wang, Raphaël M. Jungers
In this paper, we consider the problem of invariant set computation for black-box switched linear systems using merely a finite set of observations of system trajectories. In parti…
Computation of the maximal invariant set of discrete-time linear systems subject to a class of non-convex constraints
Zheming Wang, Raphaël M. Jungers, Chong-Jin Ong
We consider the problem of computing the maximal invariant set of discrete-time linear systems subject to a class of non-convex constraints that admit quadratic relaxations. These…
Data-driven computation of invariant sets of discrete time-invariant black-box systems
Zheming Wang, Raphaël M. Jungers
We consider the problem of computing the maximal invariant set of discrete-time black-box nonlinear systems without analytic dynamical models. Under the assumption that the system…
Speeding up finite-time consensus via minimal polynomial of a weighted graph - a numerical approach
Zheming Wang, Chong Jin Ong
Reaching consensus among states of a multi-agent system is a key requirement for many distributed control/optimization problems. Such a consensus is often achieved using the standa…
Economic MPC of Nonlinear Systems with Non-Monotonic Lyapunov Functions and Its Application to HVAC Control
Zheming Wang, Guoqiang Hu
This paper proposes a Lyapunov-based economic MPC scheme for nonlinear sytems with non-monotonic Lyapunov functions. Relaxed Lyapunov-based constraints are used in the MPC formulat…