Control Parameter Optimization for Feedback-Controlled Underwater Gliders Operating in Offshore Wind Farms

Operating underwater gliders near offshore wind farms with strong ocean currents is challenging, as excessive intervention by the feedback controller can lead to increased energy consumption. This study establishes an evaluation framework for the energy consumption and motion accuracy of feedback-controlled underwater gliders. By employing the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Pareto optimality, the controller parameters are optimized to achieve a balance between energy efficiency and motion accuracy. A case study is conducted to validate the effectiveness of the proposed methodology.