Erquan Wang

Mr. Erquan Wang

orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 March 2024 in Drones
Verified
Journal Article
Open access
PDF file
EWErquan Wang
Erquan Wang
JSJinyang Sun
Jinyang Sun
YLYuanyuan Liang
Yuanyuan Liang
BZBoyu Zhou
Boyu Zhou
FJFangfei Jiang
Fangfei Jiang
YZYang Zhu
Yang Zhu
This paper investigates the problem of cooperative payload delivery by two quadrotors with a novel “Y”-shaped cable that improves payload carrying and dropping efficiency. Compared with the existing “V”-shaped suspension, the proposed suspension method adds another payload swing degree of freedom to the quadrotor–payload system, making the modeling and control of such a system more challenging. In the modeling, the payload swing motion is decomposed into a forward–backward process and a lateral process, and the swing motion is then transmitted to the dynamics of the two quadrotors by converting it into disturbance cable pulling forces. A novel guidance and control framework is proposed, where a guidance law is designed to not only achieve formation transformation but also generate a local reference for the quadrotor, which does not have access to the global reference, based on which a cooperative controller is developed by incorporating an uncertainty and disturbance estimator to actively compensate for payload swing disturbance to achieve the desired formation trajectory tracking performance. A singular perturbation theory-based analysis shows that the proposed parameter mapping method, which unifies the parameter tuning of different control channels, allows us to tune a single parameter, ε, to quantitatively enhance both the formation control performance and system robustness. Simulation results verify the effectiveness of the proposed approach in different scenarios.

16 January 2025 in Drones
Verified
Journal Article
Open access
PDF file
ZZZhiyuan Zheng
Zhiyuan Zheng
世仝世纪 仝
世纪 仝
EWErquan Wang
Erquan Wang
YZYang Zhu
Yang Zhu
JSJinliang Shao
Jinliang Shao
In practice, the consensus performance of a multi-UAV system can degrade significantly due to the presence of measurement noise and disturbances. However, simultaneously rejecting the noise and disturbances to achieve high-precision consensus tracking control is rather challenging. In this paper, to address this issue, we propose a novel distributed consensus tracking control framework consisting of a distributed observer and a local dual-estimator-based tracking controller. Each UAV’s distributed observer estimates the leader’s states and generates the local reference, functioning even under a switching communication topology. In the local tracking controller design, we reveal that classic uncertainty and disturbance estimator (UDE)-based control can magnify the noise. By combining the measurement error estimator (MEE) with UDE, a local robust tracking controller is designed to reject noise and disturbances simultaneously. The parameter tuning of MEE and UDE is unified into a single parameter, and the monotonic relationship between this parameter and system performance is revealed by the singular perturbation theorem. Finally, the validity of the proposed control framework is verified by both simulation and comparative real-world experiments.