Power, Control, and Data Processing Systems

Power, Control, and Data Processing Systems

Finite Time Power Regulation of BDFIG Using Adaptive Nonlinear Method

Document Type : Original Research

Authors
Vahid Behnamgol 1
Mohsen Ehsani 2
Ashknaz Oraee 3
Rohollah Barzamini 4
Behnaz Sohani 5
1 Energy Research Center, Islamic Azad University , Damavand Branch
2 Islamic Azad University, Damavand Branch
3 Sadjad University of Technology
4 Department of Electrical Engineering, Central Tehran Branch, Islamic Azad University
5 Wolfson School of Mechanical, Electrical & Manufacturing Engineering, Loughborough University
10.30511/pcdp.2025.2055897.1020
Abstract
This paper presents a novel finite-time adaptive dynamic sliding mode controller (SMC) for regulating the power of a brushless double-fed induction generator (BDFIG). Wind turbines equipped with BDFIGs present unique challenges due to the system's nonlinear dynamics, external disturbances, and inherent uncertainties. To address these issues, SMC is employed for its robustness and effectiveness in uncertain environments. The proposed controller integrates a dynamic SMC, ensuring a smooth control signal and mitigating the chattering effect commonly associated with conventional SMCs. A key innovation of this work is the development of an adaptive gain mechanism that eliminates the need for prior knowledge of uncertainty bounds. This adaptive gain dynamically converges to the upper bound of uncertainties, enhancing the system's adaptability and robustness. Using the Lyapunov stability theorem, finite-time convergence is rigorously proven, ensuring that the sliding variable reaches zero within a finite time, and the adaptive gain aligns with the uncertainty bound.
Keywords
BDFIG
Dynamic Control
Adaptive SMC
Finite-time Stability

Subjects

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Power, Control, and Data Processing Systems
Volume 2, Issue 2
Spring 2025
Pages 11-19

  • Receive Date 13 March 2025
  • Revise Date 25 March 2025
  • Accept Date 03 April 2025
  • First Publish Date 03 April 2025
  • Publish Date 01 June 2025