Zobrazeno 1 - 10
of 402
pro vyhledávání: '"Guillaume, O."'
We investigate the problem of fitting piecewise affine functions (PWA) to data. Our algorithm divides the input domain into finitely many polyhedral regions whose shapes are specified using a user-defined template such that the data points in each re
Externí odkaz:
http://arxiv.org/abs/2305.08686
We present an algorithmic framework for the identification of candidate invariant subspaces for switched linear systems. Namely, the framework allows to compute an orthonormal basis in which the matrices of the system are close to block-triangular ma
Externí odkaz:
http://arxiv.org/abs/2209.05320
This paper presents a counterexample-guided iterative algorithm to compute convex, piecewise linear (polyhedral) Lyapunov functions for uncertain continuous-time linear hybrid systems. Polyhedral Lyapunov functions provide an alternative to commonly
Externí odkaz:
http://arxiv.org/abs/2206.11176
We study the problem of synthesizing polyhedral Lyapunov functions for hybrid linear systems. Such functions are defined as convex piecewise linear functions, with a finite number of pieces. We first prove that deciding whether there exists an $m$-pi
Externí odkaz:
http://arxiv.org/abs/2204.06693
We study the algorithmic complexity of the problem of deciding whether a Linear Time Invariant dynamical system with rational coefficients has bounded trajectories. Despite its ubiquitous and elementary nature in Systems and Control, it turns out tha
Externí odkaz:
http://arxiv.org/abs/2108.00728
Autor:
Berger, Guillaume O., Rabi, Maben
Efficient computation of trajectories of switched affine systems becomes possible, if for any such hybrid system, we can manage to efficiently compute the sequence of switching times. Once the switching times have been computed, we can easily compute
Externí odkaz:
http://arxiv.org/abs/2104.12682
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 state feedback using only a finite set of observations of trajectories wit
Externí odkaz:
http://arxiv.org/abs/2103.10823
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 respect to the initial (unknown) optimization problem. Even though our
Externí odkaz:
http://arxiv.org/abs/2101.01415
Publikováno v:
In IFAC PapersOnLine 2024 58(11):31-36
In this paper, we study the problem of stabilizing switched linear systems when only limited information about the state and the mode of the system is available, which occurs in many applications involving networked switched systems (such as cyber-ph
Externí odkaz:
http://arxiv.org/abs/2009.04715