Distributed Event‐Triggered Moving Horizon Estimation for Remote Monitoring of Bus Active Suspension Systems Over Relay Networks

ABSTRACT This paper addresses the problem of remote state estimation for active suspension systems (ASSs) in electric buses and proposes a novel distributed moving horizon estimation (DMHE) algorithm. To reduce computational complexity, the full‐vehicle ASS is decomposed into several interconnected low‐order subsystems. An event‐triggered mechanism (ETM) is introduced to reduce unnecessary data transmissions from the ASS to the remote monitoring platform. Besides, filter‐and‐forward relays are employed to improve communication reliability. On this basis, a distributed moving horizon estimator is constructed, which integrates measurements and relay data to estimate the system state. Furthermore, in view of the coupling between subsystems, a consensus cost is developed to improve estimation accuracy. Sufficient conditions are derived to guarantee the boundedness of the estimation error. Finally, the effectiveness of the proposed algorithm is verified through co‐simulations in CarSim/Simulink and experiments on a half‐vehicle ASS.

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Publication Details

Journal
Asian Journal of Control
Published
2026-09-11
DOI
https://doi.org/10.1002/asjc.70244
Primary Topic
Vibration Control and Rheological Fluids
Type
article
Field-Weighted Citation Impact
0.00

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article

Distributed Event‐Triggered Moving Horizon Estimation for Remote Monitoring of Bus Active Suspension Systems Over Relay Networks

Chenhui Xu, Defeng He, Haiping Du, Xiulan Song
Asian Journal of Control
Vibration Control and Rheological Fluids
article

Distributed Event‐Triggered Moving Horizon Estimation for Remote Monitoring of Bus Active Suspension Systems Over Relay Networks

Chenhui Xu, Defeng He, Haiping Du, Xiulan Song
article en

Abstract

ABSTRACT This paper addresses the problem of remote state estimation for active suspension systems (ASSs) in electric buses and proposes a novel distributed moving horizon estimation (DMHE) algorithm. To reduce computational complexity, the full‐vehicle ASS is decomposed into several interconnected low‐order subsystems. An event‐triggered mechanism (ETM) is introduced to reduce unnecessary data transmissions from the ASS to the remote monitoring platform. Besides, filter‐and‐forward relays are employed to improve communication reliability. On this basis, a distributed moving horizon estimator is constructed, which integrates measurements and relay data to estimate the system state. Furthermore, in view of the coupling between subsystems, a consensus cost is developed to improve estimation accuracy. Sufficient conditions are derived to guarantee the boundedness of the estimation error. Finally, the effectiveness of the proposed algorithm is verified through co‐simulations in CarSim/Simulink and experiments on a half‐vehicle ASS.

Asian Journal of Control
University of Wollongong (AU), Zhejiang University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 16%
Vibration Control and Rheological Fluids
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