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The question of the stability of unstable states of dynamical systems that do not explicitly contain a small parameter, chaos and bifurcations in them has attracted attention ever since [1-14]. This is due to the fact that this problem…

Adaptation and Self-Organizing Systems · Physics 2018-10-05 Valentin Shironosov

This paper deals with the computation of polytopic invariant sets for polynomial dynamical systems. An invariant set of a dynamical system is a subset of the state space such that if the state of the system belongs to the set at a given…

Optimization and Control · Mathematics 2015-03-17 Mohamed Amin Ben Sassi , Antoine Girard

We consider the problem of adaptive stabilization for discrete-time, multi-dimensional linear systems with bounded control input constraints and unbounded stochastic disturbances, where the parameters of the true system are unknown. To…

Systems and Control · Electrical Eng. & Systems 2023-04-04 Seth Siriya , Jingge Zhu , Dragan Nešić , Ye Pu

This paper considers the problem of robust stability for a class of uncertain nonlinear quantum systems subject to unknown perturbations in the system Hamiltonian. The nominal system is a linear quantum system defined by a linear vector of…

Quantum Physics · Physics 2016-11-17 Ian R. Petersen

We provide out-of-sample certificates on the controlled invariance property of a given set with respect to a class of black-box linear systems. Specifically, we consider linear time-invariant models whose state space matrices are known only…

Optimization and Control · Mathematics 2022-02-17 Filippo Fabiani , Kostas Margellos , Paul J. Goulart

In this work we addressed the problem of stability analysis for an uncertain piecewise affine model of a genetic regulatory network. In particular we considered polytopic parameter uncertainties on the proteins production rate functions,…

Systems and Control · Electrical Eng. & Systems 2019-07-01 Mirko Pasquini , David Angeli

We consider solving linear optimization (LO) problems with uncertain objective coefficients. For such problems, we often employ robust optimization (RO) approaches by introducing an uncertainty set for the unknown coefficients. Typical RO…

Optimization and Control · Mathematics 2023-12-04 Ayaka Ueta , Mirai Tanaka , Ken Kobayashi , Kazuhide Nakata

We develop an indirect-adaptive model predictive control algorithm for uncertain linear systems subject to constraints. The system is modeled as a polytopic linear parameter varying system where the convex combination vector is constant but…

Systems and Control · Computer Science 2015-09-25 Stefano Di Cairano

The use of available disturbance predictions within a nominal model predictive control formulation is studied. The main challenge that arises is the loss of recursive feasibility and stability guarantees when a persistent disturbance is…

Systems and Control · Computer Science 2018-07-31 Pablo R Baldivieso-Monasterios , Paul A. Trodden

In the present work, a simple algorithm for stabilizing an unknown linear time-invariant system is proposed, assuming only that this system is stabilizable. The suggested algorithm is based on first performing a partial identification of…

Optimization and Control · Mathematics 2022-11-14 Dennis Gramlich , Christian Ebenbauer

Super-stability and strong stability are properties of a matching in the stable matching problem with ties. In this paper, we introduce a common generalization of super-stability and strong stability, which we call non-uniform stability.…

Computer Science and Game Theory · Computer Science 2024-08-30 Naoyuki Kamiyama

We consider the linear complementarity problem with uncertain data modeled by intervals, representing the range of possible values. Many properties of the linear complementarity problem (such as solvability, uniqueness, convexity, finite…

Optimization and Control · Mathematics 2025-10-07 Milan Hladík

We examine the issue of stability of probability in reasoning about complex systems with uncertainty in structure. Normally, propositions are viewed as probability functions on an abstract random graph where it is implicitly assumed that…

Artificial Intelligence · Computer Science 2017-12-14 Subhash Kak

Randomly-assembled dynamical systems are theoretically predicted to be unstable upon crossing a critical threshold of complexity, as first shown by May. Yet, empirical complex systems exhibit remarkable stability, indicating the presence of…

Disordered Systems and Neural Networks · Physics 2026-03-31 Francesco Ferraro , Christian Grilletta , Amos Maritan , Samir Suweis , Sandro Azaele

We survey classical and recent developments in numerical linear algebra, focusing on two issues: computational complexity, or arithmetic costs, and numerical stability, or performance under roundoff error. We present a brief account of the…

Computational Complexity · Computer Science 2010-06-22 Olga Holtz , Noam Shomron

This paper presents a new paradigm to stabilize uncertain stochastic linear systems. Herein, second moment polytopic (SMP) systems are proposed that generalize systems with both uncertainty and randomness. The SMP systems are characterized…

Optimization and Control · Mathematics 2024-10-28 Yuji Ito , Kenji Fujimoto

The paper contains a discussion on a number of open problems in queueing theory. Some of them are known for decades, some are more recent. They relate to stability and to rare events. There is an idea to prepare a special issue of QUESTA on…

Probability · Mathematics 2009-09-03 Sergey Foss

This paper deals with developing tests for checking whether an unknown system has certain structural properties. The tests that we are aiming at are in terms of noisy input-state-output data obtained from the unknown system. Since, in…

Optimization and Control · Mathematics 2020-10-30 Jaap Eising , Harry Trentelman

We consider the adaptive control problem for discrete-time, nonlinear stochastic systems with linearly parameterised uncertainty. Assuming access to a parameterised family of controllers that can stabilise the system in a bounded set within…

Systems and Control · Electrical Eng. & Systems 2025-11-24 Seth Siriya , Jingge Zhu , Dragan Nešić , Ye Pu

State convergence is essential in several scientific areas, e.g. multi-agent consensus/disagreement, distributed optimization, monotone game theory, multi-agent learning over time-varying networks. This paper is the first on state…

Optimization and Control · Mathematics 2019-10-02 Filippo Fabiani , Giuseppe Belgioioso , Franco Blanchini , Patrizio Colaneri , Sergio Grammatico