A new robust continuous-time optimization algorithm for distributed problems is presented
which guarantees fixed-time convergence. The algorithm is based on a Lyapunov function …

This article addresses the cooperative fault-tolerant control problem for networks of
stochastic nonlinear systems with actuator faults and input saturation. The fuzzy neural …

In many specific scenarios, accurateand practical cooperative learning is a commonly
encountered challenge in multi-agent systems. Thus, the current investigation focuses on …

Information compression is essential to reduce communication cost in distributed
optimization over peer-to-peer networks. This article proposes a communication-efficient …

In this paper, the optimal consensus control problem of the discrete-time multi-agent systems
with switching topologies and input delays is investigated by adopting the adaptive dynamic …

Communication efficiency is a major bottleneck in the applications of distributed networks.
To address the problem, the problem of quantized distributed optimization has attracted a lot …

Distributed optimization algorithms have various advantages and wide applications, while
the distributed nature also makes them flimsy in the face of external attacks. In this paper two …

This paper focuses on solving the problem of composite constrained convex optimization
with a sum of smooth convex functions and non-smooth regularization terms (ℓ 1 norm) …

Distributed optimization is manifesting great potential in multiple fields, eg, machine
learning, control, resource allocation, etc. Existing decentralized optimization algorithms …

In this article, we consider a multi-node sharing problem, where each node possesses a
local smooth function that is further considered as the average of several constituent …