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Sliding Mode Control with Disturbance Estimation for Underwater Robot
conference contribution
posted on 2022-03-24, 09:41 authored by Naoki Motoi, Daigo Hirayama, Fumito Yoshimura, Adham Sabra, Wai Keung FungWai Keung FungThis 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. 2022Link to Conference Website
Published in
2022 IEEE 17th International Conference on Advanced Motion Control (AMC)Publisher
IEEEPublication Date
2022-02-20Publication Year
2022Version
- 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/AMC51637.2022.9729280Print ISSN
1943-6572Electronic ISSN
1943-6580ISBN
978-1-7281-7711-3Cardiff Met Affiliation
- Cardiff School of Technologies
Cardiff Met Authors
Wai Keung FungCardiff Met Research Centre/Group
EUREKA Robotics CentreCopyright Holder
- © The Publisher
Publisher Rights Statement
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