Traditionally, offline optimization of power systems is acceptable due to the largely
predictable loads and reliable generation. The increasing penetration of fluctuating …

This paper focuses on investigating the nonsmooth resource allocation problem based on
distributed dynamical systems over state-dependent communication networks. Taking into …

By time discretization of a second-order primal–dual dynamical system with damping α/t
where an inertial construction in the sense of Nesterov is needed only for the primal …

This article studies the finite-time (FT) convergence of a fast primal–dual gradient dynamics
(PDGD), called FT-PDGD, for solving constrained optimization with general constraints and …

This article proposes a finite-time converging proximal dynamic model (FPD) to deal with
equilibrium problems. A distinctive feature of the FPD is its fast and finite-time convergence …

Second-order dynamical systems are important tools for solving optimization problems, and
most of the existing works in this field have focused on unconstrained optimization problems …

In this article, we establish the local and global exponential convergence of a primal–dual
dynamics (PDD) for solving equality-constrained optimization problems without strong …

Dual decomposition is widely utilized in the distributed optimization of multiagent systems. In
practice, the dual decomposition algorithm is desired to admit an asynchronous …

Primal-dual dynamics (PDD) and its variants are prominent first-order continuous-time
algorithms to determine the primal and dual solutions of a constrained optimization problem …

For a class of nonsmooth composite optimization problems with linear equality constraints,
we utilize a Lyapunov-based approach to establish the global exponential stability of the …