Title :
Consensus-based distributed receding horizon estimation of sensor networks
Author :
Huiping Li ; Yang Shi
Author_Institution :
Dept. of Mech. Eng., Univ. of Victoria, Victoria, BC, Canada
Abstract :
This paper is concerned with the consensus-based distributed receding horizon estimation (RHE) problem of sensor networks. Firstly, a distributed optimization problem is formulated for each sensor node based on its state and its neighboring information. The explicit solution to each optimization problem is provided, based on which the consensus-based distributed RHE algorithm is designed. The sufficient condition under which the state estimates of all the sensor nodes can reach robust consensus is developed. We show that, under the designed consensus-based estimator, the estimation error of each sensor node converges to a set.
Keywords :
estimation theory; optimisation; state estimation; wireless sensor networks; RHE problem; consensus-based distributed RHE algorithm; consensus-based distributed receding horizon estimation; designed consensus-based estimator; distributed optimization problem; estimation error; neighboring information; sensor networks; sensor nodes; state estimation; sufficient condition; Algorithm design and analysis; Estimation error; Kalman filters; Nickel; Optimization; Robustness; Distributed estimation; receding horizon estimation; sensor networks;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an