Distributed controller-estimator for target tracking of networked robotic systems under sampled interaction
This work addresses coordination challenges in robotic networks for applications like surveillance or search, but it appears incremental as it builds on existing distributed control methods.
The paper tackles target tracking for networked robotic systems with sampled interactions by proposing two distributed controller-estimator algorithms, achieving practical stability of tracking error with conditions on topology and sampling periods, as demonstrated through simulations.
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.