Motion control of unmanned underwater vehicles via deep imitation reinforcement learning algorithm-Reference-Cited by-同舟云学术

Motion control of unmanned underwater vehicles via deep imitation reinforcement learning algorithm

Published:2020-05 Issue:7 Volume:14 Page:764-774
ISSN:1751-9578
Container-title:IET Intelligent Transport Systems
language:en
Short-container-title:IET Intelligent Transport Systems

Author:

Chu Zhenzhong¹^ORCID,Sun Bo¹,Zhu Daqi¹,Zhang Mingjun²,Luo Chaomin³

Affiliation:

1. Shanghai Engineering Research Center of Intelligent Maritime Search & Rescue and Underwater VehiclesShanghai Maritime UniversityShanghai201306People's Republic of China

2. College of Mechanical and Electrical Engineering, Harbin Engineering UniversityHarbin150001People's Republic of China

3. Department of Electrical and Computer EngineeringMississippi State UniversityMississippiMS39762USA

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-its.2019.0273

Reference23 articles.

1. An adaptive SOM neural network method for distributed formation control of a group of AUVs;Li X.;IEEE Trans. Ind. Electron.,2018

2. Fuzzy observer‐based prescribed performance control of vehicle roll behavior via controllable damper;Wang Z.;IEEE Access,2019

3. Impact of current disturbances on AUV docking: model‐based motion prediction and countering approaches;Fan S.;Ocean. Eng.,2018

4. Yaw and lateral stability control for four‐wheel steer‐by‐wire system;Zhao W.;IEEE/ASME Trans. Mechatronics,2018

5. Path‐following control of an AUV: A multi objective model predictive control approach;Shen C.;IEEE Trans. Control Syst. Technol.,2019

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