Results 61 to 70 of about 78,251 (234)

Scaling diagram for the localization length at a band edge

open access: yes, 2007
A weak-coupling scaling diagram for the Lyapunov exponent and the integrated density of states near a band edge of a random Jacobi matrix is obtained. The analysis is based on the use of a Fokker-Planck operator describing the drift-diffusion of the Pr ...
Sadel, Christian, Schulz-Baldes, Hermann
core   +3 more sources

Spectrum of Lyapunov exponents in non-smooth systems evaluated using orthogonal perturbation vectors

open access: yesMATEC Web of Conferences, 2018
This paper covers application of the novel method of Lyapunov exponents (LEs) spectrum estimation in non smooth mechanical systems. In the presented method, LEs are obtained from a Poincaré map.
Balcerzak Marek   +3 more
doaj   +1 more source

“It Is Much Safer to Be Sparse than Connected”: Safe Control of Robotic Swarm Density Dynamics with PDE Optimization with State Constraints

open access: yesAdvanced Intelligent Systems, EarlyView.
This paper proposes a novel control framework to ensure safety of a robotic swarm. A feedback optimization controller is capable of driving the swarm toward a target density while keeping risk‐zone exposure below a safety threshold. Theory and experiments show how safety is more effectively achieved for sparsely connected swarms.
Longchen Niu, Gennaro Notomista
wiley   +1 more source

Theory and computation of covariant Lyapunov vectors

open access: yes, 2012
Lyapunov exponents are well-known characteristic numbers that describe growth rates of perturbations applied to a trajectory of a dynamical system in different state space directions.
A. Trevisan   +38 more
core   +1 more source

On $\Psi$-bounded solutions for non-homogeneous matrix Lyapunov systems on $\mathbb{R}$

open access: yesElectronic Journal of Qualitative Theory of Differential Equations, 2009
In this paper we provide necesssary and sufficient conditions for the existence of at least one $\Psi$-bounded solution on $\mathbb{R}$ for the system $X'=A(t)X +XB(t)+F(t)$, where $F(t)$ is a Lebesgue $\Psi$-integrable matrix valued function on ...
M. S. N. Murty, Grande Suresh Kumar
doaj   +1 more source

Controlling Dynamical Systems Into Unseen Target States Using Machine Learning

open access: yesAdvanced Intelligent Systems, EarlyView.
Parameter‐aware next‐generation reservoir computing enables efficient, data‐driven control of dynamical systems across unseen target states and nonstationary transitions. The approach suppresses transient behavior while navigating system collapse scenarios with minimal training data—over an order of magnitude less than traditional methods.
Daniel Köglmayr   +2 more
wiley   +1 more source

Computational Issues in Nonlinear Dynamical Systems: Creating Bifurcation Diagrams of Lyapunov Exponents Using a Novel Adaptive Approach

open access: yesIEEE Access
Nonlinear dynamical systems with oscillatory (periodic, quasi-periodic and chaotic) responses are analyzed in this paper through the method of Lyapunov exponents.
Maciej Walczak, Wieslaw Marszalek
doaj   +1 more source

Wearable exoskeleton robot control using radial basis function‐based fixed‐time terminal sliding mode with prescribed performance

open access: yesAsian Journal of Control, EarlyView.
Abstract This paper tackles the problem of robust and accurate fixed‐time tracking in human–robot interaction and deals with uncertainties. This work introduces a control approach for a wearable exoskeleton designed specifically for rehabilitation tasks.
Mahmoud Abdallah   +4 more
wiley   +1 more source

Robust Control Theory for Time Lag System in Chemical Engineering and Its Application

open access: yesChemical Engineering Transactions, 2017
A series of problems of the time-lag system including robust stability analysis and guaranteed cost controller design are studied mainly based on the Lyapunov stability theory by linear matrix inequality method and time lag partitioning method in this ...
Mingli Zhou
doaj   +1 more source

Risk‐aware safe reinforcement learning for control of stochastic linear systems

open access: yesAsian Journal of Control, EarlyView.
Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili   +2 more
wiley   +1 more source

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