期刊
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
卷 19, 期 1, 页码 122-142出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TASE.2021.3069779
关键词
Fuels; Resource management; Optimization; Propellers; Attitude control; Minimization; Surges; Fuel consumption optimization; marine dynamic positioning (DP) systems; near real-time optimization; thrust allocation problem
Marine dynamic positioning (DP) systems are crucial for maintaining vessel position and heading in offshore operations. Optimal thrust allocation can significantly reduce fuel consumption, and current methods can solve this problem in near real-time.
In offshore maritime operations, automated systems capable of maintaining the vessel's position and heading using its own propellers and thrusters to compensate exogenous disturbances, like wind, waves, and currents, are referred to as marine dynamic positioning (DP) Systems. DP systems play a central role in several marine operations, such as drilling, pipe-laying, coring, and ocean observation. These operations are the primary cause of fuel consumption, having a strong impact on the overall footprint of the vessel. For this reason, we will face the problem of optimal thrust allocation of an over-actuated vessel to maintain position and heading with minimal fuel consumption. State-of-the-art approaches simplify this problem by roughly approximating it and obtain a simple, mostly convex, optimization problem that can be solved in near-real time by the automation system. In this article, we improve current approaches with the following contributions. We will exploit a higher fidelity representation of the physical system, and we will manipulate the resulting optimization problem accordingly, to allow for near-real-time solutions on conventional computing platforms on-board. We evaluate the quality of the proposal with a case study on a drilling unit equipped with six thrusters. The results will show that it is possible to achieve up to 5% of fuel savings with respect to conventional approaches.
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