Anti-disturbance fixed-time formation control of multi-AUVs via event-triggered strategy

被引:0
|
作者
Su B. [1 ,2 ]
Wang H.-B. [1 ,2 ]
Gao J. [1 ,2 ]
机构
[1] College of Electrical Engineering, YanShan University, Qinhuangdao
[2] Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao
关键词
Disturbance observer; Event-triggered mechanism; Fixedtime control; Formation control; Virtual leader-follower method;
D O I
10.7641/CTA.2021.00524
中图分类号
学科分类号
摘要
To tackle with the problem of model parameter uncertainty and external disturbance of multi-AUVs formation control, an event-triggered formation strategy based on fixed-time fuzzy disturbance observer is developed, which can ensure formation control converges within a fixed time. First of all, fixed time fuzzy disturbance observer is constructed to approximate compound disturbance accurately. Based on the disturbance observer, this method combines with command filter and the back-stepping theory, which is borrowed to remove large amount of calculation caused by repeated derivative. Secondly, the event trigger mechanism is introduced into the multi-AUVs formation control for the purpose of saving network transmission resources and reduce controller transmission energy consumption. The distributed formation controller with fixed time convergence performance is designed, and the system convergence time is related to the controller design parameters. Finally, the effectiveness and rationality of the designed algorithm are proved by the multi-AUVs formation simulation experiment. © 2021, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
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页码:1113 / 1123
页数:10
相关论文
共 26 条
  • [1] WANG J, WANG C, WEI Y, Et al., Command filter based adaptive neural trajectory tracking control of an underactuated underwater vehicle in three-dimensional space, Ocean Engineering, 180, pp. 175-186, (2019)
  • [2] BRAGINSKY B, BARUCH A, GUTERMAN H., Development of an autonomous surface vehicle capable of tracking autonomous underwater vehicles, Ocean Engineering, 197, pp. 106-868, (2020)
  • [3] YANG T T, YU S H, YAN Y., Formation control of multiple underwater vehicles subject to communication faults and uncertainties, Applied Ocean Research, pp. 109-116, (2019)
  • [4] LI Juan, YUAN Ruikun, ZHANG Honghan, Research on multiple AUVs formation control algorithm based on leader-follower method, Chinese Journal of Scientific Instrument, 40, 6, pp. 237-246, (2019)
  • [5] GAO Zhengyu, GUO Ge, Fixed-time formation control of AUVs based on a disturbance observer, Acta Automatica Sinica, 45, 6, pp. 1094-1102, (2019)
  • [6] XING L, WEN C, GUO F, Et al., Event-based consensus for linear multi-agent systems without continuous communication, IEEE Transactions on Cybernetics, 47, 8, pp. 2132-2142, (2017)
  • [7] HUA C C, LI K, GUAN X P., Event-based dynamic output feedback adaptive fuzzy control for stochastic nonlinear systems, IEEE Transactions on Fuzzy Systems, 26, 5, pp. 3004-3015, (2018)
  • [8] CHRISTOPHE V, SYLVAIN B, MICHEL K, Et al., Distributed eventtriggered control strategies for multi-agent formation stabilization and tracking, Automatica, 106, pp. 110-116, (2019)
  • [9] LIU J, ZHANG Y, YU Y, Et al., Fixed-time event-triggered consensus for nonlinear multi-agent systems without continuous communications, IEEE Transactions on Systems, Man, and Cybernetics, 49, 11, pp. 2221-2229, (2019)
  • [10] SONG L, WANG H Q, LIU P X P., Fixed-time adaptive eventtriggered tracking control of uncertain nonlinear systems, Nonlinear Dynamics, 100, 1, pp. 3381-3397, (2020)