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Linear systems on Lie groups are a natural generalization of linear system on Euclidian spaces. For such systems, this paper studies controllability by taking in consideration the eigenvalues of an associated derivation D. When the state…

Optimization and Control · Mathematics 2016-01-05 Adriano Da Silva

This paper addresses questions regarding controllability for `generic parameter' dynamical systems, i.e. the question whether a dynamical system is `structurally controllable'. Unlike conventional methods that deal with structural…

Optimization and Control · Mathematics 2010-06-29 Madhu N. Belur , Sivaramakrishnan Sivasubramanian

This paper proposes an algorithm capable of driving a system to follow a piecewise linear trajectory without prior knowledge of the system dynamics. Motivated by a critical failure scenario in which a system can experience an abrupt change…

Robotics · Computer Science 2025-10-06 Taha Shafa , Yiming Meng , Melkior Ornik

Determining the reachable set for a given nonlinear control system is crucial for system control and planning. However, computing such a set is impossible if the system's dynamics are not fully known. This paper is motivated by a scenario…

Optimization and Control · Mathematics 2021-08-26 Taha Shafa , Melkior Ornik

A method to generate new classes of random matrix ensembles is proposed. Random matrices from these ensembles are Lax matrices of classically integrable systems with a certain distribution of momenta and coordinates. The existence of an…

Chaotic Dynamics · Physics 2011-09-26 E. Bogomolny , O. Giraud , C. Schmit

Random matrix ensembles are introduced that respect the local tensor structure of Hamiltonians describing a chain of $n$ distinguishable spin-half particles with nearest-neighbour interactions. We prove a central limit theorem for the…

Mathematical Physics · Physics 2017-06-19 J. P. Keating , N. Linden , H. J. Wells

Many models for chaotic systems consist of joining two integrable systems with incompatible constants of motion. The quantum counterparts of such models have a propagator which factorizes into two integrable parts. Each part can be…

Chaotic Dynamics · Physics 2009-10-31 Tomaz Prosen , Thomas H. Seligman , Hans A. Weidenmueller

Flexible systems are linear systems of inclusions in which the elements of the coefficient matrix are external numbers in the sense of nonstandard analysis. External numbers represent real numbers with small, individual error terms. Using…

Numerical Analysis · Mathematics 2023-02-27 Nam Van Tran , Imme van den Berg

Linear systems on Lie groups are a natural generalization of linear system on Euclidian spaces. For such systems, this paper studies the properties of the maximal sets of approximate controllability.

Dynamical Systems · Mathematics 2016-02-18 Adriano Da Silva , Victor Ayala , Guilherme Zsigmond

Random matrix theory is a well-developed area of probability theory that has numerous connections with other areas of mathematics and its applications. Much of the literature in this area is concerned with matrices that possess many exact…

Probability · Mathematics 2018-06-22 Ramon van Handel

This work addresses controllability properties for some systems of partial differential equations in which the main feature is the coupling through nonlocal integral terms. In the first part, we study a nonlinear parabolic-elliptic system…

Analysis of PDEs · Mathematics 2023-12-07 Kuntal Bhandari , Víctor Hernández-Santamaría

We study random matrices with independent subgaussian columns. Assuming each column has a fixed Euclidean norm, we establish conditions under which such matrices act as near-isometries when restricted to a given subset of their domain. We…

Probability · Mathematics 2025-09-05 Yaniv Plan , Roman Vershynin

The paper is focused on the discussion of the phenomenon of transitional chaos in dynamic autonomous and non-autonomous systems. This phenomenon involves the disappearance of chaotic oscillations in specific time periods and the system…

Chaotic Dynamics · Physics 2026-02-10 Marek Berezowski

The paper continues the authors' study of the linearizability problem for nonlinear control systems. In the recent work [K. Sklyar, Systems Control Lett. 134 (2019), 104572], conditions on mappability of a nonlinear control system to a…

Optimization and Control · Mathematics 2021-01-26 Katerina V. Sklyar , Svetlana Yu. Ignatovich

Seemingly unrelated linear regression models are introduced in which the distribution of the errors is a finite mixture of Gaussian components. Identifiability conditions are provided. The score vector and the Hessian matrix are derived.…

Methodology · Statistics 2014-03-18 Giuliano Galimberti , Elena Scardovi , Gabriele Soffritti

Determining the distance between a controllable system to the set of uncontrollable systems, namely, the controllability radius problem, has been extensively studied in the past. However, the opposite direction, that is, determining the…

Optimization and Control · Mathematics 2022-09-07 Yuan Zhang , Yuanqing Xia , Yufeng Zhan , Zhongqi Sun

In this paper we introduce the $\epsilon$ - revised system associated to a Hamilton - Poisson system. The $\epsilon$ - revised system of the rigid body with three linear controls is defined and some of its geometrical and dynamical…

Symplectic Geometry · Mathematics 2007-05-23 Dan Comanescu , Mihai Ivan , Gheorghe Ivan

This paper deals with strong structural controllability of linear structured systems in which the system matrices are given by zero/nonzero/arbitrary pattern matrices. Instead of assuming that the nonzero and arbitrary entries of the system…

Optimization and Control · Mathematics 2020-03-05 Jiajia Jia , Harry L. Trentelman , Nikolaos Charalampidis , M. Kanat Camlibel

A new class of Random Matrix Ensembles is introduced. The Gaussian orthogonal, unitary, and symplectic ensembles GOE, GUE, and GSE, of random matrices are analogous to the classical Gibbs ensemble governed by Boltzmann's distribution in the…

Statistical Mechanics · Physics 2019-07-03 Maciej M. Duras

In this paper we propose a stochastic model predictive control (MPC) algorithm for linear discrete-time systems affected by possibly unbounded additive disturbances and subject to probabilistic constraints. Constraints are treated in…

Systems and Control · Computer Science 2019-02-15 Lukas Hewing , Melanie N. Zeilinger