Le Wang

Dr. Le Wang


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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Verified
Journal Article
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LWLe Wang
Le Wang
QWQing Wu
Qing Wu
Jialun LiuJialun Liu
Jialun Liu
SLShijie Li
Shijie Li
RNRudy R. Negenborn
Rudy R. Negenborn
At present, with the development of waterborne transport vehicles, research on ship faces a new round of challenges in terms of intelligence and autonomy. The concept of maritime autonomous surface ships (MASS) has been put forward by the International Maritime Organization in 2017, in which MASS become the new focus of the waterborne transportation industry. This paper elaborates on the state-of-the-art research on motion control of MASS. Firstly, the characteristics and current research status of unmanned surface vessels in MASS and conventional ships are summarized, and the system composition of MASS is analyzed. In order to better realize the self-adaptability of the MASS motion control, the theory and algorithm of ship motion control-related systems are emphatically analyzed under the condition of classifying ship motion control. Especially, the application of intelligent algorithms in the ship control field is summarized and analyzed. Finally, this paper summarizes the challenges faced by MASS in the model establishment, motion control algorithms, and real ship experiments, and proposes the composition of MASS motion control system based on variable autonomous control strategy. Future researches on the accuracy and diversity of developments and applications to MASS motion control are suggested.


30 January 2023 in Advances in Engineering Software
Verified
Journal Article
Closed access
LWLe Wang
Le Wang
SLShijie Li
Shijie Li
Jialun LiuJialun Liu
Jialun Liu
YHYuanchao Hu
Yuanchao Hu
QWQing Wu
Qing Wu

30 March 2022 in Ocean Engineering
Verified
Journal Article
Closed access
LWLe Wang
Le Wang
SLShijie Li
Shijie Li
Jialun LiuJialun Liu
Jialun Liu
QWQing Wu
Qing Wu
RNRudy R. Negenborn
Rudy R. Negenborn

16 December 2019 in IEEE Access
Verified
Journal Article
Open access
LWLe Wang
Le Wang
QWQing Wu
Qing Wu
Jialun LiuJialun Liu
Jialun Liu
SLShijie Li
Shijie Li
RNRudy R. Negenborn
Rudy R. Negenborn
Intelligent motion control is one of the key technologies of ships. This paper studies the application of Adaptive Mutation Beetle Particle Swarm (AMBPS)-PID algorithm in ship motion control. Firstly, the ship MMG model is established. Then the BAS algorithm is introduced, and AMBPS algorithm is improved and designed on this basis. Secondly, ship heading and path following controllers are designed according to the algorithm, and rudder turning rate constraint is introduced to limit the rudder angle. Thirdly, through the test function effect analysis of AMBPS and other similar algorithms, the improved effect of this algorithm is verified. Finally, from manual tuning PID parameters to off-line and on-line optimizing parameters based on AMBPS algorithm, the optimal control parameters are obtained step by step, and the optimal heading and path following simulation results are achieved. Compared with the results of traditional PID, AMBPS-PID algorithm has a better adaptive control effect on ship motion control, reduces the error of manual tuning parameters and improves efficiency.

10 March 2022 in International Journal of Naval Architecture and Ocean Engineering
Verified
Journal Article
Open access
LWLe Wang
Le Wang
SLShijie Li
Shijie Li
Jialun LiuJialun Liu
Jialun Liu
QWQing Wu
Qing Wu