Adaptive hierarchical model predictive control of wave energy converters.

Overview

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, the project team 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 combined the strengths of MPC and adaptive control and thus could outperform 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 sub-structured system (DSS), which has more advantages than the conventional hardware-in-the-loop testing method.

As the project moved into Stage 2, the 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. The control framework proposed in Stage 1 was also developed further, and its efficacy was validated thoroughly by numerical simulations. The Stage 2 simulation results showed that performance of the Mocean WEC could be improved by 10% to 90% in most sea states. This improvement was 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 states.

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 non-causal feed-forward information to model predictive control (MPC) to improve performance.

According to the sea state, a weighting function was tuned for the MPC controller and the WEC model was also 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, adaptive control, and deterministic wave prediction technique and thus outperforms the strength of any single MPC or adaptive control strategy. This control framework was developed for a typical attenuator type of WEC as a case study and its efficacy  experimentally validated using an efficient and economically viable test rig.

In Stage 3, the aim of the project was to contribute a technology that allows a significant reduction in the through life installed capacity cost of wave energy converters (WECs) applicable to a wide range of WEC hull and power take-off (PTO) designs. To achieve this objective, the efficacy of the control techniques successfully developed in Stage 1 and Stage 2 were experimentally validated in a hardware in the loop (HIL) environment. Further to this, the techniques were validated by implementing them on a fully representative scaled WEC system, i.e. the existing 1/20th scale physical model attenuator type WEC developed by Mocean Energy Ltd. The control techniques developed in this project can be straightforwardly extended to other types of WECs.

Further evidence based on experimental results was provided to validate the main numerical results of Stage 2, to confirm the benefits of our control techniques and quantitatively compare their performance with the existing baseline control techniques. This contributes towards delivering a design outline for broader WEC control systems to provide a generic guideline for WEC controller selection, design and tuning.