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author:

Miao, Baobin (Miao, Baobin.) [1] | Li, Tieshan (Li, Tieshan.) [2] | Luo, Weilin (Luo, Weilin.) [3] (Scholars:罗伟林)

Indexed by:

EI Scopus

Abstract:

In this paper, a novel adaptive neural network (NN) controller is proposed for trajectory tracking of autonomous underwater vehicles (AUVs) in the presence of model errors and external disturbance. A command filtered technique is used to tackle the problem of 'explosion of complexity' inherent in the conventional backstepping method. Furthermore, the norm of the ideal weighting vector in neural network systems is considered as the estimation parameter, such that only one parameter is adjusted. It is also shown that the proposed NN based adaptive robust controller can guarantee the uniformly ultimately bounded of the AUV systems. Finally a numerical example is given to demonstrate the validity of the results. © 2014 TCCT, CAA.

Keyword:

Adaptive control systems Autonomous underwater vehicles Backstepping Controllers Neural networks Nonlinear systems

Community:

  • [ 1 ] [Miao, Baobin]Navigational College, Dalian Maritime University, Dalian; 116026, China
  • [ 2 ] [Li, Tieshan]Navigational College, Dalian Maritime University, Dalian; 116026, China
  • [ 3 ] [Luo, Weilin]College of Mechanical Engineering and Automation, Fuzhou University, Fujian; 350108, China

Reprint 's Address:

  • [miao, baobin]navigational college, dalian maritime university, dalian; 116026, china

Email:

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Source :

ISSN: 1934-1768

Year: 2014

Page: 8011-8016

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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