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author:

Tian, Y. (Tian, Y..) [1] | Li, T. (Li, T..) [2] | Miao, B. (Miao, B..) [3] | Luo, W. (Luo, W..) [4]

Indexed by:

Scopus

Abstract:

In this paper, robust adaptive tracking control is proposed for the autonomous underwater vehicle (AUV) in the presence of external disturbance. Backstepping control of the system dynamics is introduced to develop full state feedback tracking control. Using backstepping control, minimal learning parameter (MLP) and variable structure control (VSC) based techniques, the robust adaptive tracking control is presented for AUV to handle the uncertainties and improve the robustness. The proposed controller guarantees that all the close-loop signals are semi-global uniform boundedness and that the tracking errors converge to a small neighborhood of the desired trajectory. Finally, simulation studies are given to illustrate the effectiveness of the proposed algorithm. © 2016 IEEE.

Keyword:

autonomous underwater vehicle; minimal learning parameter; neural network; trajectory tracking

Community:

  • [ 1 ] [Tian, Y.]Navigational College, Dalian Maritime University, Dalian, 116026, China
  • [ 2 ] [Li, T.]Navigational College, Dalian Maritime University, Dalian, 116026, China
  • [ 3 ] [Miao, B.]Navigational College, Dalian Maritime University, Dalian, 116026, China
  • [ 4 ] [Luo, W.]College of Mechanical Engineering and Automation, Fuzhou University, Fujian, 350108, China

Reprint 's Address:

  • [Li, T.]Navigational College, Dalian Maritime UniversityChina

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Source :

Proceedings of the 8th International Conference on Advanced Computational Intelligence, ICACI 2016

Year: 2016

Page: 372-377

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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