3D printed negative stiffness meta-structures with superior energy absorption and super-elastic shape-recovery features
The aim of this paper is to create novel 3D cubic negative stiffness (NS) structures (NSSs)
with superior mechanical performances such as high energy absorption, shape recovery …
with superior mechanical performances such as high energy absorption, shape recovery …
LMI Conditions for Analysis: A Step Towards Design
Recently, k-contraction has been proposed as a generalization of contraction properties for
nonlinear time-variant systems. Existing tools for k-contraction analysis exploit complex …
nonlinear time-variant systems. Existing tools for k-contraction analysis exploit complex …
Further results on incremental input-to-state stability based on contraction-metric analysis
In this paper, we study the notion of incremental stability for continuous-time nonlinear
systems forced by some external input. Thanks to the notion of “Killing vector field”, we …
systems forced by some external input. Thanks to the notion of “Killing vector field”, we …
Contracting dynamics for time-varying convex optimization
In this article, we provide a novel and broadly-applicable contraction-theoretic approach to
continuous-time time-varying convex optimization. For any parameter-dependent contracting …
continuous-time time-varying convex optimization. For any parameter-dependent contracting …
From contraction theory to fixed point algorithms on Riemannian and non-Euclidean spaces
The design of fixed point algorithms is at the heart of monotone operator theory, convex
analysis, and of many modern optimization problems arising in machine learning and …
analysis, and of many modern optimization problems arising in machine learning and …
Non-Euclidean contractivity of recurrent neural networks
A Davydov, AV Proskurnikov… - 2022 American Control …, 2022 - ieeexplore.ieee.org
Critical questions in dynamical neuroscience and machine learning are related to the study
of recurrent neural networks and their stability, robustness, and computational efficiency …
of recurrent neural networks and their stability, robustness, and computational efficiency …
The Yakubovich S-Lemma revisited: Stability and contractivity in non-Euclidean norms
The celebrated S-Lemma was originally proposed to ensure the existence of a quadratic
Lyapunov function in the Lur'e problem of absolute stability. A quadratic Lyapunov function …
Lyapunov function in the Lur'e problem of absolute stability. A quadratic Lyapunov function …
Pinning control of hypergraphs
A standard assumption in control of network dynamical systems is that its nodes interact
through pairwise interactions, which can be described by means of a directed graph …
through pairwise interactions, which can be described by means of a directed graph …
Anytime Solvers for Variational Inequalities: the (Recursive) Safe Monotone Flows
A Allibhoy, J Cortés - arXiv preprint arXiv:2311.09527, 2023 - arxiv.org
This paper synthesizes anytime algorithms, in the form of continuous-time dynamical
systems, to solve monotone variational inequalities. We introduce three algorithms that solve …
systems, to solve monotone variational inequalities. We introduce three algorithms that solve …
-Contraction in a Generalized Lurie System
We derive a sufficient condition for-contraction in a generalized Lurie system (GLS), that is,
the feedback connection of a nonlinear dynamical system and a memoryless nonlinear …
the feedback connection of a nonlinear dynamical system and a memoryless nonlinear …