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Stochastic programs where the uncertainty distribution must be inferred from noisy data samples are considered. The stochastic programs are approximated with distributionally-robust optimizations that minimize the worst-case expected cost…

Optimization and Control · Mathematics 2024-01-04 Farhad Farokhi

This contribution proposes a recursive, computationally efficient, ready-to-use, online method for the ellipsoidal state characterization for linear discrete-time models with additive unknown disturbances vectors (bounded by known possibly…

Systems and Control · Electrical Eng. & Systems 2021-04-28 Yasmina Becis-Aubry

Despite the celebrated success of stochastic control approaches for uncertain systems, such approaches are limited in the ability to handle non-Gaussian uncertainties. This work presents an adaptive robust control for linear uncertain…

Optimization and Control · Mathematics 2026-01-13 Xuehui Ma , Shiliang Zhang , Zhiyong Sun , Xiaohui Zhang , Sabita Maharjan

This paper proposes a model predictive controller for discrete-time linear systems with additive, possibly unbounded, stochastic disturbances and subject to chance constraints. By computing a polytopic probabilistic positively invariant set…

Optimization and Control · Mathematics 2024-09-23 Kai Wang , Kiet Tuan Hoang , Sébastien Gros

In this paper, we introduce a method for approximating the solution to inference and optimization tasks in uncertain and deterministic reasoning. Such tasks are in general intractable for exact algorithms because of the large number of…

Artificial Intelligence · Computer Science 2012-12-12 David Ephraim Larkin

One of the most important problems in hybrid systems is the {\em reachability problem}. The reachability problem has been shown to be undecidable even for a subclass of {\em linear} hybrid systems. In view of this, the main focus in the…

Logic in Computer Science · Computer Science 2009-09-29 D. Ravi , R. K. Shyamasundar

This paper considers a disturbance attenuation problem for a linear discrete time invariant system under random disturbances with imprecisely known probability distributions. The statistical uncertainty is measured in terms of relative…

Systems and Control · Computer Science 2015-03-19 Michael M. Tchaikovsky , Alexander P. Kurdyukov , Victor N. Timin

We estimate convex polytopes and general convex sets in $\mathbb R^d,d\geq 2$ in the regression framework. We measure the risk of our estimators using a $L^1$-type loss function and prove upper bounds on these risks. We show that, in the…

Statistics Theory · Mathematics 2012-11-16 Victor-Emmanuel Brunel

Reachability analysis of hybrid systems has been used as a safety verification tool to assess offline whether the state of a system is capable of remaining within a designated safe region for a given time horizon. Although it has been…

Optimization and Control · Mathematics 2014-04-24 Kendra Lesser , Meeko Oishi

In this paper we examine how Lagrangian techniques can be used to compute underapproximations and overapproximation of the finite-time horizon, stochastic reach-avoid level sets for discrete-time, nonlinear systems. This approach is…

Systems and Control · Computer Science 2018-10-17 Joseph D. Gleason , Abraham P. Vinod , Meeko M. K. Oishi

We present a method to compute the stochastic reachability safety probabilities for high-dimensional stochastic dynamical systems. Our approach takes advantage of a nonparametric learning technique known as conditional distribution…

Systems and Control · Electrical Eng. & Systems 2020-10-19 Adam J. Thorpe , Vignesh Sivaramakrishnan , Meeko M. K. Oishi

In this paper, we consider discrete-time non-linear stochastic dynamical systems with additive process noise in which both the initial state and noise distributions are uncertain. Our goal is to quantify how the uncertainty in these…

Systems and Control · Electrical Eng. & Systems 2025-05-19 Steven Adams , Eduardo Figueiredo , Luca Laurenti

In this note, we propose a method to under-approximate finite-time reachable sets and tubes for a class of continuous-time linear uncertain systems. The class under consideration is the linear time-varying (LTV) class with integrable…

Systems and Control · Electrical Eng. & Systems 2020-02-12 Mohamed Serry

This work proposes an algorithm to bound the minimum distance between points on trajectories of a dynamical system and points on an unsafe set. Prior work on certifying safety of trajectories includes barrier and density methods, which do…

Optimization and Control · Mathematics 2023-06-16 Jared Miller , Mario Sznaier

Chance constrained program where one seeks to minimize an objective over decisions which satisfy randomly disturbed constraints with a given probability is computationally intractable. This paper proposes an approximate approach to address…

Computation · Statistics 2019-12-23 Xun Shen , Jiancang Zhuang , Xingguo Zhang

We consider an unconstrained continuous optimization problem where, in each iteration, gradient estimates may be arbitrarily corrupted with a probability greater than 1/2. Additionally, function value estimates may exhibit heavy-tailed…

Optimization and Control · Mathematics 2025-11-25 Katya Scheinberg , Miaolan Xie

An important mathematical tool in the analysis of dynamical systems is the approximation of the reach set, i.e., the set of states reachable after a given time from a given initial state. This set is difficult to compute for complex systems…

Machine Learning · Computer Science 2023-09-19 Abdelmouaiz Tebjou , Goran Frehse , Faïcel Chamroukhi

This contribution proposes a recursive set-membership method for the ellipsoidal state characterization for discrete-time linear time-varying models with additive unknown disturbances vectors, bounded by possibly degenerate zonotopes and…

Systems and Control · Electrical Eng. & Systems 2023-09-15 Yasmina Becis-Aubry

Reachable set computation is an important technique for the verification of safety properties of dynamical systems. In this paper, we investigate reachable set computation for discrete nonlinear systems based on parallelotope bundles. The…

Systems and Control · Electrical Eng. & Systems 2021-07-08 Edward Kim , Stanley Bak , Parasara Sridhar Duggirala

This paper addresses the problem of optimally controlling nonlinear systems with norm-bounded disturbances and parametric uncertainties while robustly satisfying constraints. The proposed approach jointly optimizes a nominal nonlinear…

Systems and Control · Electrical Eng. & Systems 2023-09-14 Antoine P. Leeman , Jerome Sieber , Samir Bennani , Melanie N. Zeilinger
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