Virtual prototype modeling and fuzzy control of the heave compensation system for a 500-ton deep-sea mining vessel

The unexpected heave motion of vessels generated by waves has always threatened the safe operation of mining vessels. The heave compensation system is a critical equipment for offshore cranes to ensure the safety and stability of the deep-sea mining vessel operation. Unfortunately, the nominal load of the mining vessel transporting minerals has become increasingly large, which has led to the dynamic performance of the heave compensation decline and a significant increase in energy consumption. To solve these problems, a semiactive heave compensation system and fuzzy logic-based controller are proposed in this paper. First, an active-passive hybrid heave compensation system is designed to reduce energy consumption greatly. The virtual prototype models of the proposed heave compensation system in a 500-ton deep-sea mining vessel are also built. Then, an adaptive tuning PID controller is developed based on the Transfer function of the heave compensation system and Mamdani-type fuzzy logic. Virtual prototype simulation results of AMESim-Simulink joint simulation illustrate that the accuracy of compensation for the four or six sea states reaches more than 90% with the proposed method and the power of the active compensation system is about 21% of the total power. Finally, the experimental results are included to demonstrate the effectiveness of the proposed semiactive heave compensation system.

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Publication Details

Journal
Transactions of the Institute of Measurement and Control
Published
2024-09-23
DOI
https://doi.org/10.1177/01423312241273806
Citations
2
Primary Topic
Hydraulic and Pneumatic Systems
Type
article
Field-Weighted Citation Impact
0.43

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article

Virtual prototype modeling and fuzzy control of the heave compensation system for a 500-ton deep-sea mining vessel

Zhouguo Hu, Yougang Sun, Yuanyuan Teng
2 citations
Transactions of the Institute of Measurement and Control
Hydraulic and Pneumatic Systems
0.43
article

Virtual prototype modeling and fuzzy control of the heave compensation system for a 500-ton deep-sea mining vessel

Zhouguo Hu, Yougang Sun, Yuanyuan Teng
article en
2 citations

Abstract

The unexpected heave motion of vessels generated by waves has always threatened the safe operation of mining vessels. The heave compensation system is a critical equipment for offshore cranes to ensure the safety and stability of the deep-sea mining vessel operation. Unfortunately, the nominal load of the mining vessel transporting minerals has become increasingly large, which has led to the dynamic performance of the heave compensation decline and a significant increase in energy consumption. To solve these problems, a semiactive heave compensation system and fuzzy logic-based controller are proposed in this paper. First, an active-passive hybrid heave compensation system is designed to reduce energy consumption greatly. The virtual prototype models of the proposed heave compensation system in a 500-ton deep-sea mining vessel are also built. Then, an adaptive tuning PID controller is developed based on the Transfer function of the heave compensation system and Mamdani-type fuzzy logic. Virtual prototype simulation results of AMESim-Simulink joint simulation illustrate that the accuracy of compensation for the four or six sea states reaches more than 90% with the proposed method and the power of the active compensation system is about 21% of the total power. Finally, the experimental results are included to demonstrate the effectiveness of the proposed semiactive heave compensation system.

Transactions of the Institute of Measurement and ControlVol. 47(10)
Tongji University (CN), Shanghai Maritime University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 42%
Hydraulic and Pneumatic Systems
0.43
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Virtual prototype modeling and fuzzy control of the heave compensation system for a 500-ton deep-sea mining vessel — Zhouguo Hu, Yougang Sun, et al. · Transactions of the Institute of Measurement and Control (2024) | TGRS Research Map | TGRS