Title :
Dynamic average consensus estimation over stochastically switching network via quantization communication
Author :
Li Dequan ; Liu Qipeng ; Wang Xiaofan
Author_Institution :
Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
In this paper, we consider the problem that a group of agents aims to compute the average of individually estimated noisy parameters by sharing information among a random network of digital links. In this scenario, the average consensus seeking is involved in a two-step procedure. First, each agent estimates the local time-varying parameters individually, and then agents average their estimations by interaction with neighbors through quantized communication. Impact of quantization on the performance of the proposed distributed algorithm is investigated. We prove that the agents´ states converge to a random variable that deviates from the average of the estimated parameters. We derive an upper bound for the asymptotic residual mean square error of the states, which captures effects of the quantization precision and the structure of the random communication networks.
Keywords :
distributed algorithms; mean square error methods; mobile agents; multi-agent systems; switching networks; asymptotic residual mean square error; average consensus seeking; digital links; distributed algorithm; dynamic average consensus estimation; local time-varying parameters; mobile autonomous agents; quantization communication; random communication networks; stochastically switching network; Estimation; Heuristic algorithms; Mean square error methods; Noise; Probabilistic logic; Quantization; Symmetric matrices; Distributed Algorithm; Dynamic Average Consensus; Quantization; Switching Network;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768