Abstract
This paper develops a fault estimation-based fixed-time fault-tolerant formation control strategy for multiple unmanned aerial vehicles under the case of sensor faults and directed connective communication topology. Four common types of sensor faults on position and velocity measurement channels are considered simultaneously, which are only assumed to be bounded. For monitoring the occurrence of sensor faults, a fault detection observer is developed using \(H_\infty\) approach. Then, the amplitude of the sensor fault is reconstructed by the modified adaptive radial basis function neural network-based cooperative fault estimation observer, which is triggered by the fault alarm from fault detection observer. Furthermore, a novel sliding mode-based distributed fault-tolerant formation controller is designed to compensate the effects of faults using the estimated fault information, where the unknown bounded fault compensation error and lumped disturbances are explicitly taken into consideration. Additionally, the fixed-time stability of the whole formation system is analyzed based on Lyapunov approach. Finally, a comparative simulation is performed to illustrate the performance and superiority of the proposed scheme.
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This work was partially supported by the National Natural Science Foundation of China (71971115) and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX19_0193).
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Bing Han, Ju Jiang and Chaojun Yu presented the idea and designed this study; Bing Han and Teng Cao conducted the simulation experiments and analyzed the experimental results. Bing Han and Chaojun Yu wrote the original draft preparation; Bing Han and Ju Jiang reviewed and edited the manuscript.
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This work was partially supported by the National Natural Science Foundation of China (71971115) and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX19_0193).
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Han, B., Jiang, J., Yu, C. et al. Distributed Fault Estimation and Fixed-Time Fault-Tolerant Formation Control for Multi-UAVs subject to Sensor Faults. J Intell Robot Syst 105, 80 (2022). https://doi.org/10.1007/s10846-022-01698-x
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DOI: https://doi.org/10.1007/s10846-022-01698-x