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Fault-Tolerant Time-Varying Elliptical Formation Control of Multiple Fixed-Wing UAVs for Cooperative Forest Fire Monitoring

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Abstract

This paper investigates the cooperative forest fire monitoring problem of multiple fixed-wing unmanned aerial vehicles (UAVs) in the presence of actuator faults during the fire monitoring mission. By using the fractional-order sliding-mode control strategy, a fault-tolerant time-varying elliptical formation control scheme is developed for multiple UAVs to monitor the elliptical spread of forest fire. To estimate the lumped disturbances induced by the external disturbances and actuator faults, sliding-mode disturbance observers are developed by introducing reference systems and sliding-mode differentiators. It is proved that all fixed-wing UAVs can be steered to elliptically monitor the forest fire and the cooperative tracking errors are uniformly ultimately bounded. Simulation results have demonstrated the effectiveness of the proposed control scheme.

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Funding

This work was supported in part by National Natural Science Foundation of China (No. 61833013, 62003162, and 62020106003), Natural Science Foundation of Jiangsu Province of China (No. BK20200416), China Postdoctoral Science Foundation (No. 2020TQ0151, 2020M681590), State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China (No. 2019-KF-23-05), 111 Project (No. B20007), and Natural Sciences and Engineering Research Council of Canada. These funds are related with the flight control or cooperative control of multiple unmanned aerial vehicles, which support this study.

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Ziquan Yu: Conceptualization, Methodology, Validation, Writing - original draft Youmin Zhang: Supervision, Discussion, Resources, Writing - review & editing Bin Jiang: Supervision, Resources Xiang Yu: Discussion, Resources

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Correspondence to Youmin Zhang.

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Yu, Z., Zhang, Y., Jiang, B. et al. Fault-Tolerant Time-Varying Elliptical Formation Control of Multiple Fixed-Wing UAVs for Cooperative Forest Fire Monitoring. J Intell Robot Syst 101, 48 (2021). https://doi.org/10.1007/s10846-021-01320-6

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