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Distributed event triggering control for six-rotor UAV systems with asymmetric time-varying output constraints

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Abstract

Inspired by the practical operability and safety of unmanned aerial vehicles (UAVs) in confined areas, this paper investigates adaptive trajectory tracking control problems in multiple six-rotor UAV systems with asymmetric time-varying output constraints and input saturation. Under model and disturbance uncertainties, six-rotor UAV systems are modeled as two non-strict-feedback systems, including attitude (inner-loop) and position (outer-loop) regulation systems. For the inner-loop design, the neural-based distributed adaptive attitude consensus control protocol is employed to realize the leader-follower consensus. Adaptive first-order sliding mode differentiators and an auxiliary dynamic system are introduced to address the “explosion of complexity” and saturation nonlinearity issues, respectively. Then, an event-triggered condition is predefined to alleviate the communication loads and reduce the number of messages to be transmitted from the controller to actuator. In addition, a class of asymmetric time-varying barrier Lyapunov functions are constructed for preventing the violation of time-varying output constraints. Accordingly, the proposed double-loop control strategies guarantee that all signals of UAV systems are semi-globally and uniformly bounded. Simulation results demonstrate that the proposed control method is effective.

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Acknowledgements

This work was partially supported by National Natural Science Foundation of China (Grant Nos. 62033003, 62003093, 61803105, U1911401), Local Innovative and Research Teams Project of Guangdong Special Support Program (Grant No. 2019BT02X353), China Postdoctoral Science Foundation (Grant No. 2020M682614), and Science and Technology Program of Guangzhou (Grant No. 201904020006).

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Correspondence to Hongru Ren.

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Cao, L., Ren, H., Meng, W. et al. Distributed event triggering control for six-rotor UAV systems with asymmetric time-varying output constraints. Sci. China Inf. Sci. 64, 172213 (2021). https://doi.org/10.1007/s11432-020-3128-2

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  • DOI: https://doi.org/10.1007/s11432-020-3128-2

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