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Sliding Mode Control with Disturbance Estimation for Underwater Robot

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conference contribution
posted on 2022-03-24, 09:41 authored by Naoki Motoi, Daigo Hirayama, Fumito Yoshimura, Adham Sabra, Wai Keung FungWai Keung Fung
This paper proposes a sliding mode control with a disturbance estimation for an underwater robot. The mobility performance of an underwater robot is influenced by modeling error, observation noise, and several disturbances such as ocean current and tidal current. Therefore, a robust control system is needed for precise motion control of an underwater robot. This paper uses a sliding mode control, which is one of the robust control methods. In a sliding mode control, chattering tends to occur, if the switching gain is set to a high value. On the other hand, it is desirable to set the switching gain high from the viewpoint of robustness. Therefore, there is a trade-off between the switching gain and robustness. In the proposed method, the disturbance is estimated in real-time, and this estimated value is added to the control input. Most of the disturbances are compensated by this estimated value, and the sliding mode control is used for the rest of the disturbances. As a result, the robust control system is achieved by using the proposed method, even if the switching gain is set to a low value. The validity of the proposed method was confirmed from the simulation and experimental results.

Funding

This work was supported in part by Hyogo Science and Technology, and JSPS KAKENHI Grant Number 19K04454

History

Presented at

IEEE 17th International Conference on Advanced Motion Control , Padova, Italy 18-20 Feb. 2022

Link to Conference Website

Published in

2022 IEEE 17th International Conference on Advanced Motion Control (AMC)

Publisher

IEEE

Publication Date

2022-02-20

Publication Year

2022

Version

  • AM (Accepted Manuscript)

Citation

Motoi, N., Hirayama, D., Yoshimura, F., Sabra, A. and Fung, W.K., (2022) Sliding Mode Control with Disturbance Estimation for Underwater Robot. In 2022 IEEE 17th International Conference on Advanced Motion Control (AMC) (pp. 317-322). IEEE. doi: 10.1109/AMC51637.2022.9729280

Print ISSN

1943-6572

Electronic ISSN

1943-6580

ISBN

978-1-7281-7711-3

Cardiff Met Affiliation

  • Cardiff School of Technologies

Cardiff Met Authors

Wai Keung Fung

Cardiff Met Research Centre/Group

EUREKA Robotics Centre

Copyright Holder

  • © The Publisher

Publisher Rights Statement

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Language

  • en

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