The project aim was to develop a reliable and efficient control strategy to improve the wave energy converter (WEC) conversion efficiency and survivability over a wide range of sea states. This was to be achieved by integrating some enabling technologies in control and wave prediction into a hierarchical control framework, so that it can be equipped with several important features: maximum energy output, robustness to modelling uncertainties, and survivability at different sea sates.

Specifically, we used a deterministic sea wave prediction technique to predict the incoming waves, and this information was used to determine the sea state and provide anti-causal feedforward information to model predictive control (MPC) to improve performance.

According to the sea state, a weighting function can be tuned for the MPC controller and the WEC model will also be adaptively updated, so that the optimal performance of the MPC controller can be maintained over a wide range of sea states. This framework combines the strengths of MPC and adaptive control and thus outperforms the strength of any single MPC or adaptive control strategy.

This control framework was developed with a typical attenuator type of WEC as a case study and its efficacy experimentally validated using an efficient and economically viable test rig developed based on the concept of dynamically substructured system (DSS), which has more advantages than the conventional hardware-in-the-loop testing method.

Queen Mary University presented a poster on their Stage 1 Control Systems project at the 2017 WES Annual Conference. All Stage 1 Control System posters are available to download here.