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We provide a fully nonlinear port-Hamiltonian formulation for discrete elastodynamical systems as well as a structure-preserving time discretization. The governing equations are obtained in a variational manner and represent index-1…

Dynamical Systems · Mathematics 2025-06-23 Philipp L. Kinon , Tobias Thoma , Peter Betsch , Paul Kotyczka

Current theories from biosocial (e.g.: the role of neurotransmitters in behavioral features), ecological (e.g.: cultural, political, and institutional conditions), and interpersonal (e.g.: attachment) perspectives have grounded…

Physics and Society · Physics 2009-11-03 Alhaji Cherif , Kamal Barley

Fluctuation formulas for elastic and viscoelastic moduli allow their computation from equilibrium molecular dynamics simulations, avoiding explicit nonequilibrium deformation protocols. While such expressions are well established for the…

Materials Science · Physics 2026-05-14 F. E. Garbuzov , Y. M. Beltukov

The data generated by long-delayed dynamical systems can be organized in patterns by means of the so-called spatio-temporal representation, uncovering the role of multiple time-scales as independent degrees of freedom. However, their…

Chaotic Dynamics · Physics 2018-12-19 Francesco Marino , Giovanni Giacomelli

Robust control of complex engineered and biological systems hinges on the integration of feedforward and feedback mechanisms. This is exemplified in neural motor control, where feedforward muscle co-contraction complements sensory-driven…

Optimization and Control · Mathematics 2026-03-06 Bastien Berret , Frédéric Jean

Non-linear dynamics is not a usually covered topic in undergraduate physics courses. However, its importance within classical mechanics and the general theory of dynamical systems is unquestionable. In this work we show that this subject…

Classical Physics · Physics 2024-08-09 Ronaldo S. S. Vieira , Luiz H. R. Daniel , Marcus A. M. de Aguiar

Existing smart composite piezoelectric beam models in the literature mostly ignore the electro-magnetic interactions and adopt the linear elasticity theory. However, these interactions substantially change the controllability and…

Optimization and Control · Mathematics 2018-03-21 Ahmet Ozkan Ozer

Robustness guarantees are important properties to be looked for during control design. They ensure stability of closed-loop systems in face of uncertainties, unmodeled effects and bounded disturbances. While the theory on robust stability…

Systems and Control · Electrical Eng. & Systems 2022-10-10 Samuele Zoboli , Daniele Astolfi , Vincent Andrieu

We introduce the construction of a orthogonal wavepacket basis set, using the concept of stroboscopic time propagation, tailored to the efficient description of non-equilibrium extended electronic systems. Thanks to three desirable…

Materials Science · Physics 2008-08-08 P. Bokes , F. Corsetti , R. W. Godby

We present an implementation of a new method for explicit simulations of time-dependent electric currents through nanojunctions. The method is based on unitary propagation of stroboscopic wave packet states and is designed to treat open…

Materials Science · Physics 2014-05-06 M. Konôpka , P. Bokes

The non-extensive statistical mechanics has been applied to describe a variety of complex systems with inherent correlations and feedback loops. Here we present a dynamical model based on previously proposed static model exhibiting in the…

Statistical Mechanics · Physics 2016-04-20 A. Kononovicius , J. Ruseckas

We investigate the stochastic resonance phenomenon in a physical system based on a tunnel diode. The experimental control parameters are set to allow the control of the frequency and amplitude of the deterministic modulating signal over an…

Statistical Mechanics · Physics 2009-10-31 Rosario N. Mantegna , Bernardo Spagnolo , Marco Trapanese

In this paper, we study connections between the classical model-based approach to nonlinear system theory, where systems are represented by equations, and the nonlinear behavioral approach, where systems are defined as sets of trajectories.…

Optimization and Control · Mathematics 2024-05-30 Antonio Fazzi , Alessandro Chiuso

As the motions of nonconservative autonomous systems are typically not periodic, the definition of nonlinear modes as periodic motions cannot be applied in the classical sense. In this paper, it is proposed 'make the motions periodic' by…

Chaotic Dynamics · Physics 2021-01-05 Malte Krack

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic…

Disordered Systems and Neural Networks · Physics 2017-07-07 Jorge G. T. Zañudo , Gang Yang , Réka Albert

This paper introduces a linear state-space model with time-varying dynamics. The time dependency is obtained by forming the state dynamics matrix as a time-varying linear combination of a set of matrices. The time dependency of the weights…

Machine Learning · Statistics 2014-10-06 Jaakko Luttinen , Tapani Raiko , Alexander Ilin

Data-driven, model-free analytics are natural choices for discovery and forecasting of complex, nonlinear systems. Methods that operate in the system state-space require either an explicit multidimensional state-space, or, one approximated…

Machine Learning · Statistics 2021-03-15 Joseph Park , Gerald M Pao , Erik Stabenau , George Sugihara , Thomas Lorimer

We propose an informal test for stationarity in a time series which checks for the compatibility of nonlinear approximations to the dynamics made in different segments of the sequence. The segments are compared directly, rather than via…

chao-dyn · Physics 2009-10-31 Thomas Schreiber

In this paper we present a direct adaptive control method for a class of uncertain nonlinear systems with a time-varying structure. We view the nonlinear systems as composed of a finite number of ``pieces,'' which are interpolated by…

Optimization and Control · Mathematics 2007-05-23 R. Ordonez , K. M. Passino

Learning-based control methods typically assume stationary system dynamics, an assumption often violated in real-world systems due to drift, wear, or changing operating conditions. We study reinforcement learning for control under…

Machine Learning · Computer Science 2026-04-03 Klemens Iten , Bruce Lee , Chenhao Li , Lenart Treven , Andreas Krause , Bhavya Sukhija