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Information 2018, 9(3), 64; https://doi.org/10.3390/info9030064

Distributed State Estimation under State Inequality Constraints with Random Communication over Multi-Agent Networks

1
Xi’an Institute of High-Tech, Xi’an 710025, China
2
Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
*
Author to whom correspondence should be addressed.
Received: 1 February 2018 / Revised: 28 February 2018 / Accepted: 7 March 2018 / Published: 13 March 2018
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Abstract

In this paper, we investigate distributed state estimation for multi-agent networks with random communication, where the state is constrained by an inequality. In order to deal with the problem of environmental/communication uncertainties and to save energy, we introduce two random schemes, including a random sleep scheme and an event-triggered scheme. With the help of Kalman-consensus filter and projection on the constrained set, we propose two random distributed estimation algorithm. The estimation of each agent is achieved by projecting the consensus estimate, which is obtained by virtue of random exchange information with its neighbors. The estimation error is shown to be bounded with probability one when the agents randomly take the measurement or communicate with their neighbors. We show the stability of proposed algorithm based on Lyapunov method and projection and demonstrate their effectiveness via numerical simulations. View Full-Text
Keywords: distributed Kalman filter; multi-agent networks; random sleep; event-triggered estimator; multi-agent systems distributed Kalman filter; multi-agent networks; random sleep; event-triggered estimator; multi-agent systems
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Hu, C.; Li, Z.; Lin, H.; He, B.; Liu, G. Distributed State Estimation under State Inequality Constraints with Random Communication over Multi-Agent Networks. Information 2018, 9, 64.

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