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Control of Launch and Recovery in Enhanced Sea-States: Part of the Launch and Recovery Co-Creation Initiative

Control of Launch and Recovery in Enhanced Sea-States: Part of the Launch and Recovery Co-Creation Initiative
增强海洋状态下的发射和回收控制:发射和回收共创计划的一部分
批准号:
EP/P022952/1
负责人:
Christopher Edwards
金额:
$56.05万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --

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中文摘要
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英文摘要
Currently many marine operations, such as the Launch and Recovery (L&R) from a mother ship of small craft, manned and unmanned air vehicles and submersibles, can only be attempted safely in sufficiently calm sea-states. As an example, the L&R of a small craft from a mothership typically involves the two vessels moving together in proximity (linked by a bow-line) before the main physical connection of the two via a crane/hoist mechanism. In many cases the wave-critical high risk elements of the overall task, i.e. the connection and subsequent hoist of the small craft to the parent vessel, only last for a few tens of seconds. Taking longer than this increases the operation at risk. Once the two craft are physically connected the operator is committed to initiate the hoisting process. In this context even the short term prediction of quiescent periods of vessel motion resulting from lower than average wave activity in otherwise large sea states, has considerable operational value and may allow L&R to be untaken safely in conditions which would currently be deemed unsuitable. Such enhanced L&R capabilities are very attractive to modern navies. In this project the research aim is to develop a novel approach to predicting a suitable time instant at which to initiate an L&R operation, together with a confidence measure (provided as advice to a human operator), and then to control the execution of the subsequent lift operation once initiated, using a novel form of Model Predictive Control (MPC). The key project deliverables are: (i) a prototype decision support system (DSS), running within a software simulator, which provides continuously updated short term predictive simulations over a finite-time horizon of all aspects of the recovery process; (ii) a controller for the actual physical hoist process. These two elements will exploit hydrodynamic vessel motion prediction models driven by wave predictions from a Deterministic Sea Wave Prediction (DSWP) system, and historical and real-time vessel motion sensor data. The DSS will initially be engaged as the small craft approaches the mothership and picks up a bow-line (a low risk activity), but is not yet attached to the hoist mechanism. The research will assume the presence on the mothership of a generic winch/crane lifting system with a single cable. The cable tension is a key controlled quantity and the maximum lifting force available is a major system specification parameter. The DSS will: (i) identify an appropriate moment to attach the hoist line and initiate hoisting during predicted quiescent periods; (ii) provide a confidence measure for the safety/success of that specific simulated lift. An appropriate time to attach and hoist will be identified by taking a snap-shot of the current state of both vessels (to use as initial conditions) together with short term predictions of the movement of the mothership to simulate whether it is possible to successfully recover the small craft using the MPC controller. The operator will then be presented with a current advice summary including confidence metrics. If as a result of this advice connection and hoisting is not initiated, the process repeats using a snapshot of the new current data. This cycle continues until the operator decides to engage the hoist (or the recovery is aborted). When connection/hoisting is actually initiated, the physical lifting phase will then employ the same MPC controller used in the simulation, exploiting predictions of the motion of the mothership, the actual real-time measured motions of both craft and a free body model of the small craft when suspended clear of the water.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
Sea trial on deterministic sea waves prediction using wave-profiling radar
利用波浪剖面雷达进行确定性海浪预测的海上试验
DOI: 10.1016/j.oceaneng.2020.107297
发表时间: 2020
期刊: Ocean Engineering
影响因子: 5
作者: [Al-Ani M]
通讯作者: Al-Ani M
Super-twisting observation for a class of Lagrangian systems
一类拉格朗日系统的超扭曲观测
DOI: --
发表时间: 2017
期刊:
影响因子: --
作者: [Edwards C]
通讯作者: Edwards C
High-Capacity Wave Energy Conversion by Multi-Float, Multi-PTO, Control and Prediction: Generalized State-Space Modelling With Linear Optimal Control and Arbitrary Headings
通过多浮子、多 PTO、控制和预测进行高容量波浪能转换:具有线性最优控制和任意航向的广义状态空间建模
DOI: 10.1109/tste.2021.3082510
发表时间: 2021
期刊: IEEE Transactions on Sustainable Energy
影响因子: 8.8
作者: [Liao Z]
通讯作者: Liao Z
An Integrated Optimal Design for Guaranteed Cost Control of Motor Driving System With Uncertainty
不确定性电机驱动系统成本保证控制综合优化设计
DOI: 10.1109/tmech.2019.2937578
发表时间: 2019
期刊: IEEE/ASME Transactions on Mechatronics
影响因子: --
作者: [Zeng T]
通讯作者: Zeng T
8
    Collaborative Research: Assessing the causes of the pyrosome invasion and persistence in the California Current Ecosystem
    • 批准号:
      2329560
    • 项目类别:
      Standard Grant
    • 资助金额:
      $30.86万
    • 财政年份:
      2024
    • 负责人:
      Christopher Edwards
    • 依托单位:
    Collaborative Research: Submesoscale frontal dynamics and exchange at an upwelling bay
    • 批准号:
      2242165
    • 项目类别:
      Standard Grant
    • 资助金额:
      $40.63万
    • 财政年份:
      2023
    • 负责人:
      Christopher Edwards
    • 依托单位:
    Integrated wind-wave control of semi-submersible floating offshore wind turbine platforms (FOWT-Control)
    • 批准号:
      EP/W009706/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $55.64万
    • 财政年份:
      2023
    • 负责人:
      Christopher Edwards
    • 依托单位:
    Robustness and adaptivity: advanced control and estimation algorithms for the transverse dynamic atomic force microscope
    • 批准号:
      EP/I034831/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $33.48万
    • 财政年份:
      2012
    • 负责人:
      Christopher Edwards
    • 依托单位:
    海外基金