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author:

Luo, Weilin (Luo, Weilin.) [1] (Scholars:罗伟林) | Cheng, Bo (Cheng, Bo.) [2]

Indexed by:

EI Scopus SCIE

Abstract:

For the trajectory tracking of underactuated autonomous underwater vehicle (AUV) subject to disturbances, a disturbance suppression and neural network (NN) compensation based control strategy is proposed. Lyapunov method is used to guide the overall design of control system. To deal with the underactuation, Light of sight (LOS) guidance is used to establish the relationship between heading angle and cross-track error. To suppress the external disturbance, L2-gain design is employed to guarantee the controller robustness. To improve the tracking accuracy, on-line neural networks with guaranteed stability are designed to identify unknown dynamics including the derivatives of virtual controls and errors induced by input saturation. Numerical simulation is performed to verify the effectiveness of the proposed control strategy. Compared with sliding mode controller (SMC) and disturbance observer approaches, the proposed controller performs better in terms of robustness and the input saturation is alleviated.

Keyword:

Disturbances L2-gain Light of sight guidance Neural networks Underactuated underwater robot

Community:

  • [ 1 ] [Luo, Weilin]Fuzhou Univ, Coll Mech Engn & Automat, Fuzhou 350108, Peoples R China
  • [ 2 ] [Cheng, Bo]Fuzhou Univ, Coll Mech Engn & Automat, Fuzhou 350108, Peoples R China
  • [ 3 ] [Luo, Weilin]Fuzhou Inst Oceanog, Fuzhou 350108, Peoples R China

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Source :

OCEAN ENGINEERING

ISSN: 0029-8018

Year: 2023

Volume: 288

4 . 6

JCR@2023

4 . 6 0 0

JCR@2023

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 1

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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