Distributed State Estimation under State Inequality Constraints with Random Communication over Multi-Agent Networks

Remote optimal state estimation over communication channels with random delays

This paper is concerned with the optimal estimation of linear systems over unreliable communication channels with random delays. The measurements are delivered without time stamp, and the probabilities of time delays are assumed to be known. Since the estimation is time-driven, the actual time delays are converted into virtual time delays among the formulation. The receiver of estimation node s...

Distributed multi-agent optimization with state-dependent communication

Abstract We study distributed algorithms for solving global optimization problems in which the objective function is the sum of local objective functions of agents and the constraint set is given by the intersection of local constraint sets of agents. We assume that each agent knows only his own local objective function and constraint set, and exchanges information with the other agents over a ...

Appendices of “ Distributed Multi - Agent Optimization with State - Dependent Communication ”

Multi-agent State Estimation

The knowledge about its operation environment is a fundamental requirements for intelligents agents acting in a dynamic world. Knowledge gathering is thus a critical functionality for any agents and it involves several problems: perception, object detection, environment structure reconstruction and so on. The state estimation problem is a general definition to describe many applications: object...

Distributed Agent-based Dynamic State Estimation over a Lossy Network

In this paper, a novel distributed agent-based dynamical system estimation strategy is proposed. Each agent has a local observation space and is interested in a specific set of system state elements. The agents have the ability of two-way communication with its neighbors (i.e., agents who share at least one state element). At a particular time instant, each agent predicts its state and makes in...