Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Boskos, Dimitris"'
In this paper, we introduce a data-driven framework for synthesis of provably-correct controllers for general nonlinear switched systems under complex specifications. The focus is on systems with unknown disturbances whose effects on the dynamics of
Externí odkaz:
http://arxiv.org/abs/2406.09704
In this article we consider the problem of tether entanglement for tethered robots. In many applications, such as maintenance of underwater structures, aerial inspection, and underground exploration, tethered robots are often used in place of standal
Externí odkaz:
http://arxiv.org/abs/2402.04909
Distributionally robust optimization (DRO) incorporates robustness against uncertainty in the specification of probabilistic models. This paper focuses on mitigating the curse of dimensionality in data-driven DRO problems with optimal transport ambig
Externí odkaz:
http://arxiv.org/abs/2310.20657
We introduce a framework for the control of discrete-time switched stochastic systems with uncertain distributions. In particular, we consider stochastic dynamics with additive noise whose distribution lies in an ambiguity set of distributions that a
Externí odkaz:
http://arxiv.org/abs/2212.14260
This paper builds Wasserstein ambiguity sets for the unknown probability distribution of dynamic random variables leveraging noisy partial-state observations. The constructed ambiguity sets contain the true distribution of the data with quantifiable
Externí odkaz:
http://arxiv.org/abs/2102.01142
The goal of this paper is to obtain online abstractions for coupled multi-agent systems in a decentralized manner. A discrete model which captures the motion capabilities of each agent is derived over a bounded time-horizon, by discretizing a corresp
Externí odkaz:
http://arxiv.org/abs/2011.10619
Ambiguity sets of probability distributions are used to hedge against uncertainty about the true probabilities of random quantities of interest (QoIs). When available, these ambiguity sets are constructed from both data (collected at the initial time
Externí odkaz:
http://arxiv.org/abs/2003.06735
Distributional ambiguity sets provide quantifiable ways to characterize the uncertainty about the true probability distribution of random variables of interest. This makes them a key element in data-driven robust optimization by exploiting high-confi
Externí odkaz:
http://arxiv.org/abs/1909.11194
This paper presents a fully automated procedure for controller synthesis for multi-agent systems under coupling constraints. Each agent is modeled with dynamics consisting of two terms: the first one models the coupling constraints and the other one
Externí odkaz:
http://arxiv.org/abs/1709.06888
This paper presents results on the solvability of the observer design problem for general nonlinear triangular systems with inputs, under weak observability assumptions. The local state estimation is exhibited by means of a delayed time-varying Luenb
Externí odkaz:
http://arxiv.org/abs/1612.00816