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Adaptive fractional‐order nonsingular fast terminal sliding mode formation control of multiple quadrotor UAVs‐based distributed estimator

Adaptive fractional‐order nonsingular fast terminal sliding mode formation control of multiple... This paper mainly solves two major problems that are unavoidable in leader–follower formation process of quadrotor UAV group: the existence of external uncertainty disturbance and communication limited between quadrotor unmanned aerial vehicle (UAV) group. To solve the problem that only one of the followers in the leader–follower formation can obtain the leader's information, an improved distributed estimator is proposed in this paper, which can accurately estimate the leader's information for each follower. In addition, in order to eliminate the influence of uncertain external disturbance on the performance of quadrotor UAV, an adaptive estimation law is designed based only on velocity and position variables. For the attitude and position subsystem of the quadrotor UAV, a sliding surface with fractional‐order term is designed. Which makes the quadrotor UAV tracking error system obtain good robustness at the stage of reaching the sliding surface and fast convergence and accurate tracking performance in the sliding stage. Based on Lyapunov stability theory, the convergence results are analyzed strictly. The results show that the algorithm can make the position distance between leader and followers converge to the desired offset. Simulation results verify the effectiveness and superiority of the control algorithm. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Asian Journal of Control Wiley

Adaptive fractional‐order nonsingular fast terminal sliding mode formation control of multiple quadrotor UAVs‐based distributed estimator

Wang, Hongbin; Li, Ning; Luo, Qianda
Asian Journal of Control , Volume Early View – Mar 5, 2023
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16 pages

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Publisher
Wiley
Copyright
© 2023 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd
ISSN
1561-8625
eISSN
1934-6093
DOI
10.1002/asjc.3043
Publisher site
See Article on Publisher Site

Abstract

This paper mainly solves two major problems that are unavoidable in leader–follower formation process of quadrotor UAV group: the existence of external uncertainty disturbance and communication limited between quadrotor unmanned aerial vehicle (UAV) group. To solve the problem that only one of the followers in the leader–follower formation can obtain the leader's information, an improved distributed estimator is proposed in this paper, which can accurately estimate the leader's information for each follower. In addition, in order to eliminate the influence of uncertain external disturbance on the performance of quadrotor UAV, an adaptive estimation law is designed based only on velocity and position variables. For the attitude and position subsystem of the quadrotor UAV, a sliding surface with fractional‐order term is designed. Which makes the quadrotor UAV tracking error system obtain good robustness at the stage of reaching the sliding surface and fast convergence and accurate tracking performance in the sliding stage. Based on Lyapunov stability theory, the convergence results are analyzed strictly. The results show that the algorithm can make the position distance between leader and followers converge to the desired offset. Simulation results verify the effectiveness and superiority of the control algorithm.

Journal

Asian Journal of Control – Wiley

Published: Mar 5, 2023

Keywords: distributed formation; distributed estimator; fractional‐order nonsingular fast terminal sliding mode control; quadrotor UAVs

References

  • Fully distributed coordination learning control of second‐order nonlinear multi‐agent systems with input saturation
    Yang, N.; Li, J.
  • A distributed adaptive scheme for multiagent systems
    Imran, I. H.; Chen, Z.; Zhu, L.; Fu, M.
  • Stabilizing a spherical pendulum on a quadrotor
    Nayak, A.; Banavar, R. N.; Maithripala, D. H. S.
  • Robust team formation control for quadrotors
    Jasim, W.; Gu, D.
  • Distributed nonlinear hTHORN: control algorithm for multi‐agent quadrotor formation flying
    Rekabi, F.; Shirazi, F. A.; Sadigh, M. J.
  • Robust motion control of quadrotors
    Liu, H.; Xi, J. X.; Zhong, Y. S.
  • Robust team formation control for quadrotors
    Jasim, W.; Gu, D.
  • Path‐following control of a quadrotor UAV with a cable‐suspended payload und er wind disturbances
    Qian, L.; Liu, H. H. T.
  • Distributed fault tolerant model predictive control for multi‐unmanned aerial vehicle system
    Zhang, B.; Sun, X.; Liu, S.
  • Time‐varying formation tracking for second‐order multi‐agent systems subjected to switching topologies with application to quadrotor formation flying
    Dong, X.; Yan, Z.; Zhang, R.; Zhong, Y.
  • A novel cooperative searching architecture for multi‐unmanned aerial vehicles under restricted communication
    Ran, H.; Sun, L.
  • A segmented energy‐based nonlinear tracking control method for quadrotor transport system
    Qi, J.; Ping, Y.; Wang, M.; Wu, C.
  • Coordinated formation control design with obstacle avoidance in three‐dimensional space
    Chang, K.; Xia, Y.; Huang, K.
  • Event‐based formation control for nonlinear multiagent systems under DoS attacks
    Tang, Y.; Zhang, D. D.; Shi, P.
  • Finite‐time formation control for linear multi‐agent systems: a motion planning approach
    Liu, Y. F.; Geng, Z. Y.
  • Flocking of multi‐agent dynamic systems with virtual leader having the reduced number of informed agents
    Atrianfar, H.; Haeri, M.
  • Leader‐following consensus of multi‐agent systems with randomly varying nonlinearities and stochastic disturbances under directed switching topologies
    Sui, X.; Yang, Y.; Zhang, S.
  • Cooperative output regulation for a group of nonlinear systems with limited information exchange: a distributed observer approach
    Huang, B.; Meng, Z
  • Decentralized finite‐time sliding mode estimators and their applications in decentralized finite‐time formation tracking
    Cao, Y.; Ren, W.; Meng, Z.
  • Distributed containment control for Lagrangian networks with parametric uncertainties under a directed graph
    Mei, J.; Rei, W.; Ma, G.
  • Distributed‐observer‐based Nash equilibrium seeking algorithm for quadratic games with nonlinear dynamics
    Huang, B.; Zou, Y.; Meng, Z.
  • Leader–follower formation control of multiple vertical takeoff and landing UAVs: distributed estimator design and accurate trajectory tracking
    Yao, Z.; Meng, Z.
  • Coordinated trajectory tracking of multiple vertical take‐off and landing UAVs
    Yao, Z.; Meng, Z.
  • Robust adaptive backstepping fast terminal sliding mode controller for uncertain quadrotor UAV
    Labbadi, M.; Cherkaoui, M.
  • Fully distributed coordination learning control of second‐order nonlinear multi‐agent systems with input saturation
    Song, T.; Fang, L.; Wang, H.
  • Continuous nonsingular terminal sliding mode control for nonlinear systems subject to mismatched terms
    Zhang, J.; Yang, J.
  • Robust fractional‐order sliding mode control design for UAVs subjected to atmospheric disturbances‐ScienceDirec
    Ataa, B.; Fes, C.; Ak, B.
  • Backstepping sliding mode trajectory tracking via extended state observer for quadrotors with wind disturbance
    Wang, H.; Li, N.; Wang, Y.; Su, B.
  • Fractional differential equations
    Liu, F.; Meerschaert, M.; Momani, S.
  • Continuous finite‐time control for robotic manipulators with terminal sliding mode
    Yu, S.; Yu, X.; Shirinzadeh, B.; Man, Z.
  • Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints
    Chen, M.; Ge, S.; Ren, B.
  • Leader–follower coordinated tracking of multiple heterogeneous lagrange systems using continuous control
    Meng, Z.; Dimarogonas, V.; Johansson, K. H.
  • Nonlinear Systems, Third Edition
    Khalil, H. K.
  • FOMCON: a MATLAB toolbox for fractional‐order system identification and control
    Tepljakov, A.; Petlenkov, E.; Belikov, J.