Title
Stochastic Bounded Consensus Tracking of Second-Order Multi-Agent Systems with Measurement Noises and Sampled-Data
Abstract
This paper investigates the stochastic bounded consensus tracking problems of second-order multi-agent systems, where the control input of an agent can only use the information measured at the sampling instants from its neighbors or the virtual leader with a time-varying reference state, and the measurements are corrupted by random noises. The probability limit theory, the algebra graph theory, and some other techniques are employed to derive the necessary and sufficient condition guaranteeing the mean square bounded consensus tracking. It turns out that the maximum allowable sampling period depends on not only the network topology but also the constant feedback gains. Furthermore, the effects of the sampling period on tracking performance, including the tracking speed and the static tracking error, are also analyzed. The results show that reducing the sampling period can accelerate the tracking speed and decrease the static tracking error. Simulations are provided to demonstrate the effectiveness of the theoretical results.
Year
DOI
Venue
2012
10.1007/s10846-012-9681-x
Journal of Intelligent and Robotic Systems
Keywords
Field
DocType
Second-order multi-agent systems,Mean square bounded consensus tracking,Measurement noises,Sampled-data
Graph theory,Mean square,Control theory,Sampling (signal processing),Multi-agent system,Network topology,Control engineering,Sampling (statistics),Mathematics,Tracking error,Bounded function
Journal
Volume
Issue
ISSN
68
3-4
0921-0296
Citations 
PageRank 
References 
2
0.37
34
Authors
4
Name
Order
Citations
PageRank
Zhihai Wu1584.00
Li Peng2263.92
Linbo Xie3192.53
Jiwei Wen4436.36