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Journal of Mechanical Science and Technology

, Volume 33, Issue 6, pp 2903–2914 | Cite as

On the fuzzy-adaptive command filtered backstepping control of an underactuated autonomous underwater vehicle in the three-dimensional space

  • JinQiang Wang
  • Cong WangEmail author
  • YingJie Wei
  • ChengJu Zhang
Article

Abstract

This paper studies the three-dimensional path following control problem for an underactuated autonomous underwater vehicle in the presence of parameter uncertainties and external disturbances. Firstly, an appropriate model for the error dynamics was established to solve the path following problem in a moving Serret-Frenet frame. Secondly, an adaptive robust control scheme is proposed through fuzzy logic theory, command filtered backstepping method and an adaptation mechanism. Finally, a suitable Lyapunov candidate function is utilized to verify the stability of the overall control system and demonstrate uniform ultimate boundedness of path following errors. Following novelties are highlighted in this study: (i) The fuzzy method is adopted to solve the problems of model uncertainties, which makes the controller more practical; (ii) to calculate the virtual control derivative, a second-order filter is designed. This reduces the computational effort of the standard backstepping technique. Moreover, the effect of high frequency measurement noise is considerably attenuated via an appropriate filter to attain a more robust control system. (iii) To attain a desired approximation accuracy between the virtual control and the filtered signals, a compensation loop containing the filtered error is established. (iv) An anti-windup design is proposed to solve the problem of integral saturation in control input signals. Finally, comparative simulations are performed to ensure that the presented control scheme has excellent following accuracy and good robustness under multiple uncertainties and external disturbances.

Keywords

Underactuated underwater vehicle Path following control Backstepping Fuzzy logic Multiple uncertainties 

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Notes

Acknowledgment

The authors acknowledge support by the National Natural Science Foundation of China (NSFC, Grant Nos. 11672094).

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Copyright information

© KSME & Springer 2019

Authors and Affiliations

  • JinQiang Wang
    • 1
  • Cong Wang
    • 1
    Email author
  • YingJie Wei
    • 1
  • ChengJu Zhang
    • 1
  1. 1.School of AstronauticsHarbin Institute of TechnologyHarbinChina

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