| OCEAN ENGINEERING | 卷:227 |
| Model predictive control for slurry pipeline transportation of a cutter suction dredger | |
| Article | |
| Wei, Changyun1,2  Wei, Yi1,2  Ji, Ze3  | |
| [1] Hohai Univ, Coll Mech & Elect Engn, Nanjing, Jiangsu, Peoples R China | |
| [2] Hohai Univ, Engn Res Ctr Dredging Technol, Minist Educ, Nanjing, Jiangsu, Peoples R China | |
| [3] Cardiff Univ, Sch Engn, Cardiff CF24 3AA, Wales | |
| 关键词: Pipeline transportation; Model predictive control; Slurry pumps; Automated control; Cutter suction dredgers; | |
| DOI : 10.1016/j.oceaneng.2021.108893 | |
| 来源: Elsevier | |
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【 摘 要 】
Cutter Suction Dredgers (CSDs) are a special type of ships designed for construction and maintenance projects of ocean and offshore engineering. During the dredging operation, CSDs can excavate nearly all kinds of soil on the sea bed, and then the dredged materials with coarse particles need to be sucked up by a slurry pump and transported to a disposal area through a long-distance pipeline. In order to avoid sedimentation of slurry in pipeline transportation, the flow rate must be maintained within a reasonable range. Otherwise, the pipeline can be blocked when the slurry density is too high. In this paper, we present a Model Predictive Control (MPC) approach to manipulate the flow rate of slurry in pipeline transportation for a CSD. To demonstrate the advantages of our proposed approach, we also implement three Proportional-Integral-Derivative (PID) controllers (i.e., conventional PID, Fuzzy-PID, and LQR-PID) to make a direct comparison. Moreover, in order to evaluate the effectiveness of our proposed approach in real scenarios, we have, in particular, built a slurry pipeline transportation platform. Both the simulation and experimental results show that our proposed MPC approach is more effective than other PID controllers in controlling the flow rate in the slurry pipeline transportation problem. The proposed approach can provide a guideline for the automated control of the slurry pump for a CSD.
【 授权许可】
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【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| 10_1016_j_oceaneng_2021_108893.pdf | 2519KB |
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