Particle swarm optimization of synergetic controller and sliding-mode extreme seeking controller for wind power generation system

粒子群优化协同控制器和滑模极值搜索控制器在风力发电系统中的应用

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Abstract

This article proposes a novel robust control strategy for Doubly Fed Induction Generator (DFIG)-based wind turbine systems by integrating Synergetic Control (SC) with Sliding Mode Extremum Seeking Control (SMESC) to enhance performance and reliability. The proposed SC-SMESC scheme replaces conventional Field-Oriented Control (FOC) with PI regulators by providing a compact and systematic formulation that ensures accurate control under both steady state and dynamic operating conditions. The architecture adopts a dual-loop design: a SC-based inner loop for high-precision active and reactive power regulation, and a SMESC-based outer loop for maximum power point tracking (MPPT). To further enhance adaptability, controller parameters are optimally tuned using a Particle Swarm Optimization (PSO) algorithm. Simulation results show that the optimized SC-SMESC strategy improves MPPT efficiency by 2%, reduces steady-state error by 77.52%, decreases settling time by 96.15%, and lowers the total harmonic distortion (THD) of stator currents to 0.63% compared to the conventional FOC-PI method. Moreover, the proposed approach exhibits strong robustness against parameter variations and external disturbances, confirming its effectiveness for high-performance wind energy conversion systems.

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