Control of Launch and Recovery in Enhanced Sea-States: Part of the Launch and Recovery Co-Creation Initiative
Lead Research Organisation:
UNIVERSITY OF EXETER
Department Name: Engineering
Abstract
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.
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.
Planned Impact
The research vision underpinning the EPSRC "Launch and Recovery Co-Creation Initiative" 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. It is generally accepted that the number of new vessels and new vessel types being planned by the UK, and indeed other navies, is modest, and thus a key focus is on upgrading the performance and service life of existing craft using new technology-based systems. This is one aspect of the EPSRC Formative Growth in manufacturing thread aimed at adding new technology based value to a new generation of UK products. The Launch and Recovery Co-Creation Initiative is atypical in so far as a high profile industrial consortium, led by BAE Systems, was engaged in this endeavour at the outset with EPSRC, and they take on the primary role of post project "push through" to higher technology readiness levels and play a key role in influencing investment from industry, the MOD and other organisations such Innovate UK, leading eventually to market.
The outputs from this proposal can be multi-tracked because a large number of commercial maritime operations in addition to naval roles can benefit from the enhanced operational control made possible by quiescent period prediction. The applicants have collaborated with Shell Trading and Supply (STASCO) exploring the problem of coupling cryogenic natural gas tankers to large floating gas collection facilities. Helicopter transfers from vessels are a vital part of day to day operations in the North Sea offshore industry, and these are directly equivalent to their naval counterparts. Less obvious is the application of Fast Robust MPC methods based on Deterministic Sea Wave prediction to renewable energy problems. To maximize the energy capture, a wave energy converter (WEC) must have a frequency response function which is the complex conjugate of the short term spectrum of the incoming wave system. This means that the WEC needs to continuously adapt its frequency response function (using active feedback), which requires predicting the incoming wave profile. Clearly this is an application of DSWP and the co-applicants have worked extensively on so called wave-by-wave tuning of WECs, and several of their publications in this area exploit Convex Optimal Control as a route to best exploit the wave predictive data while minimising the cost of WEC systems. Hence the future market demand for ever more effective cheaper wave RADARs arising from maritime operations enabled by the outcomes of the planned research during the Launch and Recovery Co-Creation Initiative, will potentially have a profound impact on reducing the cost of wave energy and help release its potential. The applicants propose to vigorously pursue this dual-tracking of the impact of the proposed project through their membership of the EPSRC funded SuperGen Marine Core.
The outputs from this proposal can be multi-tracked because a large number of commercial maritime operations in addition to naval roles can benefit from the enhanced operational control made possible by quiescent period prediction. The applicants have collaborated with Shell Trading and Supply (STASCO) exploring the problem of coupling cryogenic natural gas tankers to large floating gas collection facilities. Helicopter transfers from vessels are a vital part of day to day operations in the North Sea offshore industry, and these are directly equivalent to their naval counterparts. Less obvious is the application of Fast Robust MPC methods based on Deterministic Sea Wave prediction to renewable energy problems. To maximize the energy capture, a wave energy converter (WEC) must have a frequency response function which is the complex conjugate of the short term spectrum of the incoming wave system. This means that the WEC needs to continuously adapt its frequency response function (using active feedback), which requires predicting the incoming wave profile. Clearly this is an application of DSWP and the co-applicants have worked extensively on so called wave-by-wave tuning of WECs, and several of their publications in this area exploit Convex Optimal Control as a route to best exploit the wave predictive data while minimising the cost of WEC systems. Hence the future market demand for ever more effective cheaper wave RADARs arising from maritime operations enabled by the outcomes of the planned research during the Launch and Recovery Co-Creation Initiative, will potentially have a profound impact on reducing the cost of wave energy and help release its potential. The applicants propose to vigorously pursue this dual-tracking of the impact of the proposed project through their membership of the EPSRC funded SuperGen Marine Core.
Publications
Al-Ani M
(2020)
Sea trial on deterministic sea waves prediction using wave-profiling radar
in Ocean Engineering
Al-Ani M
(2021)
On Fully Describing the Probability Distribution of Quiescent Periods From Sea Spectral Density
in IEEE Journal of Oceanic Engineering
Edwards C
(2019)
Enhanced continuous higher order sliding mode control with adaptation
in Journal of the Franklin Institute
Edwards C
(2017)
Super-twisting observation for a class of Lagrangian systems
Kong L
(2018)
Adaptive fuzzy control for a marine vessel with time-varying constraints
in IET Control Theory & Applications
Liao Z
(2021)
High-Capacity Wave Energy Conversion by Multi-Float, Multi-PTO, Control and Prediction: Generalized State-Space Modelling With Linear Optimal Control and Arbitrary Headings
in IEEE Transactions on Sustainable Energy
Liao Z
(2023)
Modelling and Control Tank Testing Validation for Attenuator Type Wave Energy Converter - Part II: Linear Noncausal Optimal Control and Deterministic Sea Wave Prediction Tank Testing
in IEEE Transactions on Sustainable Energy
Rout V
(2024)
Control of the launch and recovery of small boats to a mothership in high sea states using sliding mode methods
in Control Engineering Practice
Description | Quiescent Period Prediction (QPP) was previously not viable as a real time sea going system due to excessive computational costs meant the time to perform a QPP estimate was longer than the prediction time. The technique described in M. Al-Ani, M. R. Belmont and J. Christmas, "Sea trial on deterministic sea waves prediction using wave-profiling radar", Ocean engineering. Vol. 207, July 2020, has reduced the computing time by an order of magnitude making real time sea going QPP viable for the first time. All our original research ambitions have been met (and in some cases exceeded). Specifically: 1. We have managed to achieve a large increase in the computational efficiency of the wave prediction scheme (as explained above) which is important for future implementations of such a system at sea. 2. The envisaged Model Predictive Control schemes have been tested in L&R simulation on a variety of ship models of differing fidelity. 3. The same Model Predictive Control technique have been applied to a different marine related problem and tank tested on floating devices over a range of realistic sea conditions. 4. A physical scale model of an L&R crane rig setup has been built, which when completed, will serve as a test-bed for hardware-in-the-loop simulations of the proposed system. This will progress the work to a higher technology readiness level. |
Exploitation Route | This technology has a wide range of civil and military marine applications, and also other offshore applications - for example wind energy generation. The maritime applications include launch and recovery of small vessels to motherships, recovery of autonomous vehicles from the ocean, landing on airborne manned and unmanned platforms on motherships, and transfer between ships at seas. It also has applications to offshore wind energy platforms to facilitate stabilization of the platform and platform inspection. |
Sectors | Aerospace Defence and Marine |
Description | Quiescent Period Prediction (QPP) was previously not viable as a real time sea going system due to excessive computational costs which meant the time to perform a QPP estimate was longer than the prediction time. Work arising from this grant has reduced the computing time by an order of magnitude making real time sea going QPP viable. The MOD have provided on-going support to the technology of QPP with multiple sea trials (including some involving the Royal Navy flagship HMS Queen Elizabeth). Most recently (2021) the Navy command initiated the first of a sequence of calls (TOF 383) to culminate in the delivery of a sea going QPP system. This was won by the Exeter Marine Dynamics group. Additionally Leonardo Helicopters commissioned a Roadmap to Market (value £45k) for a QPP based helicopter launch and recovery system. They have incorporated the recommended system into their primary flight simulator. |
First Year Of Impact | 2021 |
Sector | Aerospace, Defence and Marine |
Impact Types | Economic |
Description | QPP |
Geographic Reach | Multiple continents/international |
Policy Influence Type | Citation in other policy documents |
Impact | Has persuaded UK Ministry of Defence to support a technology demonstrator |
Description | Adaptive hierarchical model predictive control of wave energy converters |
Amount | £739,000 (GBP) |
Organisation | Wave Energy Scotland |
Sector | Private |
Country | United Kingdom |
Start | 08/2017 |
End | 05/2021 |
Description | Energy Catalyst Round 8: clean energy access, feasibility projects |
Amount | £252,218 (GBP) |
Funding ID | Application number: 86116 |
Organisation | Innovate UK |
Sector | Public |
Country | United Kingdom |
Start | 09/2021 |
End | 09/2022 |
Description | Integrated wind-wave control of semi-submersible floating offshore wind turbine platforms (FOWT-Control) |
Amount | £436,700 (GBP) |
Funding ID | EP/W009706/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 05/2023 |
End | 06/2026 |
Description | LiDAR Ship Trial |
Amount | £192,000 (GBP) |
Funding ID | LiDAR Ship Trial on RFA Tanker Tide Force. TOF 260, |
Organisation | Ministry of Defence (MOD) |
Sector | Public |
Country | United Kingdom |
Start | 01/2019 |
End | 12/2019 |
Description | Marie Curie ITN |
Amount | € 3,932,721 (EUR) |
Organisation | European Union |
Sector | Public |
Country | European Union (EU) |
Start | 09/2017 |
End | 09/2021 |
Description | QPP Development |
Amount | £86,000 (GBP) |
Funding ID | TOF383 |
Organisation | Ministry of Defence (MOD) |
Sector | Public |
Country | United Kingdom |
Start | 01/2021 |
End | 04/2021 |
Description | System-level Co-design and Control of Large Capacity Wave Energy Converters with Multiple PTOs |
Amount | £522,969 (GBP) |
Funding ID | EP/V040650/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 11/2021 |
End | 10/2022 |
Description | UK Ministry of defence, Primed by Babock international |
Amount | £192,000 (GBP) |
Funding ID | TOF 260 |
Organisation | Ministry of Defence (MOD) |
Sector | Public |
Country | United Kingdom |
Start | 02/2019 |
End | 07/2019 |
Description | Honorary Professorship at Exeter University |
Organisation | Hoffman Engineering |
Country | United States |
Sector | Private |
PI Contribution | Bernard Ferrier of head of the Dynamic Interface Laboratory at Hoffman Engineering USA was made an honorary Professor at Exeter University. Interactions leading to publications and joint applications for further funding. |
Collaborator Contribution | Bernard Ferrier of head of the Dynamic Interface Laboratory at Hoffman Engineering USA was made an honorary Professor at Exeter University. He delivered a public lecture at Exeter University. |
Impact | Interactions leading to publications and joint applications for further funding. |
Start Year | 2019 |
Description | Quiescent Period Simulator |
Organisation | Westland Helicopters Ltd |
Country | United Kingdom |
Sector | Private |
PI Contribution | The main simulator used by Westland helicopters for launch and recovery from ships was equipped with a quiescent period simulator directly based on Exeter QPP research |
Collaborator Contribution | Westland Helicopters have acted as a mentor helping take QPP to the market |
Impact | Help in securing funding for UK MOD for sea trials and for securing a grant of £86000 from the Naval Design Partnership primed by Babcock international |
Start Year | 2018 |
Description | Bernard Ferrier public lecture |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Undergraduate students |
Results and Impact | This was a public lecture providing an introduction to the lecturers specific area of research, recent successes and future directions |
Year(s) Of Engagement Activity | 2019 |
Description | Deployed QPP System |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Since the Exeter Marine Dynmaics group pioneered research into quiescent Period Prediction there ahs been growing interest from industry and the UL Ministry of Defence which has eventually culminated in planning a programme to deliver a sea going system. |
Year(s) Of Engagement Activity | Pre-2006,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020 |