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Open AccessArticle
Event-Triggered Neural Adaptive Distributed Cooperative Control for the Multi-Tug Towing of Unactuated Offshore Platform with Uncertainties and Unknown Disturbances
by
Shaolong Geng
Shaolong Geng 1,
Yulong Tuo
Yulong Tuo 1,2,*
,
Yuanhui Wang
Yuanhui Wang 3,
Zhouhua Peng
Zhouhua Peng 1,2 and
Shasha Wang
Shasha Wang 1,2
1
College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China
2
Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships, Dalian 116026, China
3
College of Intelligent System Science and Engineering, Harbin Engineering University, Harbin 150001, China
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2024, 12(8), 1242; https://doi.org/10.3390/jmse12081242 (registering DOI)
Submission received: 30 May 2024
/
Revised: 19 July 2024
/
Accepted: 22 July 2024
/
Published: 23 July 2024
Abstract
An event-triggered neural adaptive cooperative control is proposed for the towing system (TS) with model parameter uncertainties and unknown disturbances. Different from ordinary multi-vessel formation control, the tugs and unactuated offshore platform in the TS are connected together by towlines, and the resultant tension of the towlines serves as the actual drag force for the platform. Initially, based on the radial basis function neural network (RBFNN), an adaptive RBFNN is designed to compensate unknown disturbances and model parameter uncertainties of the TS, and we use minimal learning parameter (MLP) algorithm to reduce the online learning parameters of adaptive RBFNN. Combined with dynamic surface technology and event-triggered control (ETC) mechanism, an event-triggered neural adaptive virtual controller is designed to obtain the desired drag force of the platform. According to the quadratic programming algorithm, the desired drag force is allocated as the desired tensions of towlines. Subsequently, the desired towline length and the desired position information of the tugs are obtained sequentially through the towline model and the position relationship between the tugs and the platform. Then, according to the desired positions of tugs, an event-triggered neural adaptive distributed cooperative controller is designed for achieving the multi-tug towing of the offshore platform. The ETC mechanism is introduced to reduce the communication burden within the TS and the execution frequency of the tugs’ thrusters. Finally, the stability of the closed-loop system is proven using the Lyapunov theory, and the ETC mechanism proves that no Zeno behavior occurs. The effectiveness of the ETC mechanism and the MLP-based adaptive RBFNN on the controllers of TS is verified through simulations and comparison analysis.
Share and Cite
MDPI and ACS Style
Geng, S.; Tuo, Y.; Wang, Y.; Peng, Z.; Wang, S.
Event-Triggered Neural Adaptive Distributed Cooperative Control for the Multi-Tug Towing of Unactuated Offshore Platform with Uncertainties and Unknown Disturbances. J. Mar. Sci. Eng. 2024, 12, 1242.
https://doi.org/10.3390/jmse12081242
AMA Style
Geng S, Tuo Y, Wang Y, Peng Z, Wang S.
Event-Triggered Neural Adaptive Distributed Cooperative Control for the Multi-Tug Towing of Unactuated Offshore Platform with Uncertainties and Unknown Disturbances. Journal of Marine Science and Engineering. 2024; 12(8):1242.
https://doi.org/10.3390/jmse12081242
Chicago/Turabian Style
Geng, Shaolong, Yulong Tuo, Yuanhui Wang, Zhouhua Peng, and Shasha Wang.
2024. "Event-Triggered Neural Adaptive Distributed Cooperative Control for the Multi-Tug Towing of Unactuated Offshore Platform with Uncertainties and Unknown Disturbances" Journal of Marine Science and Engineering 12, no. 8: 1242.
https://doi.org/10.3390/jmse12081242
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