Adaptive Hierarchical Model Predictive Control (AHMPC) for WEC control


Stage 2

Project Lead

Queen Mary University of London

Project Sub-Contractors

University of Exeter, Mocean Energy Ltd

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 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.

Control Systems Stage 2 - Public Report - Queen Mary University of London

Control Systems Stage 2 Public Report for the Queen Mary University of London "Adaptive hierarchical model predictive control of wave energy converters (AHMPC)" project. Includes a description of the technology, scope of work, achievements and recommendations for further work.

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