Distributed controller-estimator for target tracking of networked robotic systems under sampled interaction

TL;DR

This paper proposes two novel distributed controller-estimator algorithms for networked robotic systems to achieve target tracking under sampled interactions, ensuring practical stability with theoretical guarantees and simulation validation.

Contribution

Introduction of two new distributed controller-estimator algorithms combining continuous and discontinuous signals for target tracking in NRSs.

Findings

Practical stability of tracking error achieved under specified conditions.

Comparison shows advantages over existing algorithms.

Simulation confirms theoretical results.

Abstract

This paper investigates the target tracking problem for networked robotic systems (NRSs) under sampled interaction. The target is assumed to be time-varying and described by a second-order oscillator. Two novel distributed controller-estimator algorithms (DCEA), which consist of both continuous and discontinuous signals, are presented. Based on the properties of small-value norms and Lyapunov stability theory, the conditions on the interaction topology, the sampling period, and the other control parameters are given such that the practical stability of the tracking error is achieved and the stability region is regulated quantitatively. The advantages of the presented DCEA are illustrated by comparisons with each other and the existing coordination algorithms. Simulation examples are given to demonstrate the theoretical results.