Disturbance observer-based model predictive visual servo control of underwater vehicles

Jian Gao; Guangjie Zhang; Puguo Wu; Weisheng Yan

doi:10.1109/OCEANSKOBE.2018.8559214

Disturbance observer-based model predictive visual servo control of underwater vehicles

Jian Gao, Guangjie Zhang, Puguo Wu, Weisheng Yan

School of Marine Science and Technology

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

In this paper, a disturbance observer-based model predictive controller (DO-MPC) is designed for image-based visual servoing (IBVS) of underwater vehicles subject to field-of-view constraint, actuator saturation, and external disturbances. In the proposed DO-MPC controller, the visual kinematic model and the approximate dynamic model are used to predict the future trajectories from the current states driven by input candidates over a certain horizon. The actuator control signals are solved online by optimizing a cost function of predicted trajectories under system constraints. With consideration of external disturbances and dynamic uncertainties, a high-gain disturbance observer is designed to estimate the modeling mismatch. The effectiveness of the proposed DO-MPC IBVS controller is verified by comparative simulations using a fully actuated underwater vehicle.

Original language	English
Title of host publication	2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538616543
DOIs	https://doi.org/10.1109/OCEANSKOBE.2018.8559214
State	Published - 4 Dec 2018
Event	2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018 - Kobe, Japan Duration: 28 May 2018 → 31 May 2018

Publication series

Name	2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018

Conference

Conference	2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018
Country/Territory	Japan
City	Kobe
Period	28/05/18 → 31/05/18

Keywords

Disturbance observer
Model predictive control
Underwater vehicles
Visual servo control

Access to Document

10.1109/OCEANSKOBE.2018.8559214

Cite this

Gao, J., Zhang, G., Wu, P., & Yan, W. (2018). Disturbance observer-based model predictive visual servo control of underwater vehicles. In 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018 Article 8559214 (2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/OCEANSKOBE.2018.8559214

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abstract = "In this paper, a disturbance observer-based model predictive controller (DO-MPC) is designed for image-based visual servoing (IBVS) of underwater vehicles subject to field-of-view constraint, actuator saturation, and external disturbances. In the proposed DO-MPC controller, the visual kinematic model and the approximate dynamic model are used to predict the future trajectories from the current states driven by input candidates over a certain horizon. The actuator control signals are solved online by optimizing a cost function of predicted trajectories under system constraints. With consideration of external disturbances and dynamic uncertainties, a high-gain disturbance observer is designed to estimate the modeling mismatch. The effectiveness of the proposed DO-MPC IBVS controller is verified by comparative simulations using a fully actuated underwater vehicle.",

keywords = "Disturbance observer, Model predictive control, Underwater vehicles, Visual servo control",

author = "Jian Gao and Guangjie Zhang and Puguo Wu and Weisheng Yan",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018 ; Conference date: 28-05-2018 Through 31-05-2018",

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Gao, J, Zhang, G, Wu, P & Yan, W 2018, Disturbance observer-based model predictive visual servo control of underwater vehicles. in 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018., 8559214, 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018, Institute of Electrical and Electronics Engineers Inc., 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018, Kobe, Japan, 28/05/18. https://doi.org/10.1109/OCEANSKOBE.2018.8559214

Disturbance observer-based model predictive visual servo control of underwater vehicles. / Gao, Jian; Zhang, Guangjie; Wu, Puguo et al.
2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8559214 (2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Gao, Jian

AU - Zhang, Guangjie

AU - Wu, Puguo

AU - Yan, Weisheng

PY - 2018/12/4

Y1 - 2018/12/4

N2 - In this paper, a disturbance observer-based model predictive controller (DO-MPC) is designed for image-based visual servoing (IBVS) of underwater vehicles subject to field-of-view constraint, actuator saturation, and external disturbances. In the proposed DO-MPC controller, the visual kinematic model and the approximate dynamic model are used to predict the future trajectories from the current states driven by input candidates over a certain horizon. The actuator control signals are solved online by optimizing a cost function of predicted trajectories under system constraints. With consideration of external disturbances and dynamic uncertainties, a high-gain disturbance observer is designed to estimate the modeling mismatch. The effectiveness of the proposed DO-MPC IBVS controller is verified by comparative simulations using a fully actuated underwater vehicle.

AB - In this paper, a disturbance observer-based model predictive controller (DO-MPC) is designed for image-based visual servoing (IBVS) of underwater vehicles subject to field-of-view constraint, actuator saturation, and external disturbances. In the proposed DO-MPC controller, the visual kinematic model and the approximate dynamic model are used to predict the future trajectories from the current states driven by input candidates over a certain horizon. The actuator control signals are solved online by optimizing a cost function of predicted trajectories under system constraints. With consideration of external disturbances and dynamic uncertainties, a high-gain disturbance observer is designed to estimate the modeling mismatch. The effectiveness of the proposed DO-MPC IBVS controller is verified by comparative simulations using a fully actuated underwater vehicle.

KW - Disturbance observer

KW - Model predictive control

KW - Underwater vehicles

KW - Visual servo control

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Y2 - 28 May 2018 through 31 May 2018

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Disturbance observer-based model predictive visual servo control of underwater vehicles

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