In recent years, machine learning methods have found numerous applications in power
systems for load forecasting, voltage control, power quality monitoring, anomaly detection …

This paper considers a nonsmooth constrained distributed convex optimization over multi-
agent systems. Each agent in the multi-agent system only has access to the information of its …

The flocking of multiple intelligent agents, inspired by the swarm behavior of natural
phenomena, has been widely used in the engineering fields such as in unmanned aerial …

In this paper, we address the distributed convex optimization problems for multi-agent
systems. In our research, it is assumed that each agent in the multi-agent system could …

In this study, we investigate the distributed convex optimisation problem of the multi-agent
system over an undirected network, in which the global objective function is the sum of all …

Realizing the distributed adaptive network construction of multi-UAV networks is an urgent
challenge, as they lack a reliable common control channel and can only maintain a limited …

This paper is concerned with a trajectory optimization problem for multiple unmanned aerial
vehicles (multi-UAV) systems, where the optimization model is constructed based on …

This paper addresses the distributed online bandit linear regression problems with privacy
protection, in which the training data are spread in a multi-agent network. Each node …

In this paper, a novel complex-valued neural network (CVNN) is proposed to investigate a
nonlinear complex-variable nonconvex optimization problem (CVNOP) subject to general …

In this paper, a convex optimization algorithm is proposed to solve the online trajectory
optimization problem of boost back of vertical take-off/vertical landing reusable launch …