Estrategia híbrida ANFIS-OTC para MPPT y reducción de vibraciones mecánicas en aerogeneradores marinos
Year: 2026
Type: article
Abstract: This paper presents a hybrid control strategy for offshore wind turbines that combines an Adaptive Neuro-Fuzzy Inference System (ANFIS) with conventional Optimal Torque Control (OTC). The main objective is to maintain maximum power point tracking (MPPT) efficiency while minimizing mechanical vibrations at the tower-top structure. While standard OTC extracts aerodynamic power effectively, it ignores structural loads. To address this limitation, an ANFIS-based adaptive gain scheduler is developed, where the controller is trained offline using a dataset generated from a multi-policy heuristic control framework that combines the OTC law with vibration-sensitive modifications. The ANFIS uses generator speed and tower-top acceleration as inputs to estimate an adaptive gain factor that modulates the OTC torque reference. In real-time operation, this gain scales the conventional OTC torque command, enabling a trade-off between MPPT performance and structural vibration mitigation. OpenFAST simulations demonstrate that the proposed controller successfully reduces mechanical load fluctuations while maintaining high MPPT performance compared to the traditional approach.
Source: Jornadas de Automática
Language: English
Topic: Wind Turbine Control Systems
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7204894604