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Adaptive Model Predictive Control of Wave Energy Converters

  • Siyuan Zhan
  • , Jing Na
  • , G. Li
  • , B. Wang

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we propose an adaptive hierarchical model predictive control (AHMPC) scheme for wave energy converters (WECs). This AHMPC enables adaptive tuning mechanism for a model predictive control (MPC) strategy by estimating the dynamics of a WEC online, so that it can recover from performance degradation of a WEC due to the dynamics variations at different sea conditions. The proposed AHMPC consists of two layers: On the top layer, an efficient cascaded estimation algorithm is developed to online identify and update the WEC model adaptively according to the change of sea states; on the bottom layer, a specially tailored MPC controller is implemented based on the updated WEC model to maximize the energy output subject to constraints for safe operation requirements. Numerical simulations are provided to show the efficacy of the proposed AHMPC scheme
Original languageUndefined
JournalIEEE Transactions on Sustainable Energy
DOIs
Publication statusPublished - 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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