A Novel Global Set-Membership Filtering Approach for Localization of Automatic Guided Vehicles
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Zhang, Y
Gu, W
Yan, H
Yang, F
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Abstract
This paper investigates the localization problem of the automatic guided vehicle (AGV) system. In order to improve the reliability and flexibility of the localization process, a distributed sensor network structure is introduced to realize the localization of the AGV. Moreover, considering the influence of unknown-but-bounded (UBB) noise and the accuracy requirements of the localization, a novel global set-membership filtering approach is proposed to obtain accurate localization results including a distributed set-membership filtering strategy and a circumscribed rectangle method. First, a distributed set-membership filtering strategy is designed to obtain local state estimation ellipsoids. Sufficient conditions for the existence of the state estimation ellipsoids are derived and a convex optimization process is developed to obtain the optimal local estimation ellipsoids. Then, a circumscribed rectangle method is proposed to fuse all local state estimation ellipsoids and obtain global set-membership filtering results. The proposed fusion method does not have a complicated optimization process, and can obtain more accurate estimation ellipsoids than local estimation results. Performance analysis verifies the effectiveness of the proposed global set-membership filtering approach.
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IEEE Transactions on Industrial Informatics
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This publication has been entered in Griffith Research Online as an advanced online version.
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Information systems
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Yang, H; Zhang, Y; Gu, W; Yan, H; Yang, F, A Novel Global Set-Membership Filtering Approach for Localization of Automatic Guided Vehicles, IEEE Transactions on Industrial Informatics, 2022