New advances in multiple autonomous aerial robots formation control technology

Xu, Yang; Luo, Delin; You, Yancheng; Duan, Haibin

doi:10.1007/s11431-018-9457-9

Cited by 4 publications

(2 citation statements)

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“…Meanwhile, only the linear terms of drag concerning the angle of attack are retained, and the higher-order terms are treated as perturbations. By substituting (4), (6), and ( 7) into (2), one can render that…”

Section: Model Transformationmentioning

confidence: 99%

“…(ii) In contrast to [5,6,17,39], a novel control-oriented UAV dynamics model in 3D space in the sensor and actuator faulty case is constructed with low-speed aerodynamics and uncertainties of thrust and aerodynamics, which makes the dynamics model more precise to describe the UAV real flight process and more practical for the cooperative controller design.…”

Section: Introductionmentioning

confidence: 99%

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Two-Layer Formation-Containment Fault-Tolerant Control of Fixed-Wing UAV Swarm for Dynamic Target Tracking

Qin,

Zhang,

Tang

et al. 2023

J. of Syst. Eng. Electron.

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This paper tackles the formation-containment control problem of fixed-wing unmanned aerial vehicle (UAV) swarm with model uncertainties for dynamic target tracking in three-dimensional space in the faulty case of UAVs ' actuator and sensor. The fixed-wing UAV swarm under consideration is organized as a "multi-leader-multi-follower " structure, in which only several leaders can obtain the dynamic target information while others only receive the neighbors' information through the communication network. To simultaneously realize the formation, containment, and dynamic target tracking, a two-layer control framework is adopted to decouple the problem into two subproblems: reference trajectory generation and trajectory tracking. In the upper layer, a distributed finite-time estimator (DFTE) is proposed to generate each UAV 's reference trajectory in accordance with the control objective. Subsequently, a distributed composite robust fault-tolerant trajectory tracking controller is developed in the lower layer, where a novel adaptive extended super-twisting (AESTW) algorithm with a finite-time extended state observer (FTESO) is involved in solving the robust trajectory tracking control problem under model uncertainties, actuator, and sensor faults. The proposed controller simultaneously guarantees rapidness and enhances the system 's robustness with fewer chattering effects. Finally, corresponding simulations are carried out to demonstrate the effectiveness and competitiveness of the proposed two-layer fault-tolerant cooperative control scheme.

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Section: Model Transformationmentioning

confidence: 99%