Launch & Recovery Enhanced Sea States
|Principal investigator:||Guang LI|
|Start: 01-08-2017 / End: 04-12-2020|
The project aims to develop a novel approach to predicting a suitable time instant at which to initiate an Launch and Recovery 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. The research overarching vision is to create the new science that can be exploited to provide the underpinnings of a new generation of high added-value products to upgrade the performance and prolong the service life of existing naval vessels.
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.