Control of Launch and Recovery in Enhanced Sea-States: Part of the Launch and Recovery Co-Creation Initiative
Lead Research Organisation:
Queen Mary University of London
Department Name: School of Engineering & Materials Scienc
Abstract
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People |
ORCID iD |
| Guang Li (Principal Investigator) |
Publications
Al-Ani M
(2021)
On Fully Describing the Probability Distribution of Quiescent Periods From Sea Spectral Density
in IEEE Journal of Oceanic Engineering
Al-Ani M
(2020)
Sea trial on deterministic sea waves prediction using wave-profiling radar
in Ocean 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
| 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 Energy |
| 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. Work arising from this grant has reduced the computing time by an order of magnitude making real time sea going QPP viable MOD have provided on-going support to the technology of (QPP) with multiple sea trials (including the flagship Queen Elizabeth). Most recently (2021) the Navy command initiated the first of a sequence of calls (TOF 383) to culminate in delivering a sea going QPP system. This was won by the Exeter Marine Dynamics group. 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. Some control techniques are being applied to resolve wave energy converter control problems for commercial partners. Numerical simulations and experiments have demonstrated their efficacies. |
| First Year Of Impact | 2020 |
| Sector | Aerospace, Defence and Marine,Energy |
| Impact Types | Economic |
| 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 | £384,521 (GBP) |
| Funding ID | EP/W009684/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 06/2023 |
| End | 03/2026 |
| 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 | 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 | Wohl Clean Growth Alliance Grants: 'Improved performance of onshore wave energy converters by control' |
| Amount | £20,000 (GBP) |
| Organisation | British Council |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 08/2021 |
| End | 08/2022 |
| Description | Collaboration with project partner University of Exeter |
| Organisation | University of Exeter |
| Department | College of Engineering, Mathematics & Physical Sciences |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | The two teams respectively from Queen Mary University of London and University of Exeter have been closely collaborating on the project since it started, through meetings and regular teleconferences. We have been developing control strategies for the Launch and Recovery Systems. |
| Collaborator Contribution | The Exeter University has been contributing to this project by providing dynamic model and contacting the industrial partners for real data and suggestions on the development of the software packages for the Launch & Recovery System. |
| Impact | This collaboration is indispensable for the project considering its multi-disciplinary feature. The outcomes of the collaboration upto now is a hydrodynamic model of the Launch and Recovery System (from Exeter) and its control-oriented model (from Queen Mary). Research papers are under preparation and in submission. |
| 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 |