A robust and computationally efficient adaptive PI controller based on Takagi-Sugeno fuzzy model for improving the dynamic behavior of DFIG-based wind turbine systems
Year: 2025
Type: article
Abstract: This paper presents a novel adaptive fuzzy proportional-integral (AFPI) controller to enhance the dynamic behavior and power quality of a doubly-fed induction generator (DFIG)-based wind turbine system in grid-connected mode. The proposed AFPI control method combines the design simplicity of the PI controller with the intelligent and adaptive structure of fuzzy logic control (FLC) to enhance the dynamic behavior of variable-speed DFIG-based wind turbine systems in various operating conditions. In this control system, the PI controller’s gains are dynamically adjusted by a fuzzy supervisory control system (FSCS) according to the system’s operating conditions, whose objective is to enhance the power quality, provide a fast dynamic response and a good robustness during uncertainties. This research paper has focused on the design of an implementable control algorithm on the programmable logic controllers (PLCs), which have stringent requirements for computational speed and memory capacity. In this context, the Takagi–Sugeno (TS) fuzzy model is proposed, as it is computationally more efficient than the Mamdani fuzzy model. Additionally, the Takagi–Sugeno (TS) fuzzy model simplifies the control system structure compared to the Mamdani type. Computer simulations were conducted using MATLAB/Simulink, and the results obtained for different operating conditions demonstrate the advantages and high control performance of the proposed control method over the Mamdani fuzzy models-based adaptive PI controller.
Source: Franklin Open
Language: English
Topic: Wind Turbine Control Systems
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,900
OpenAlex ID: W4416594841