Adaptive Robust Control for Pump-Controlled Pitch Systems Facing Wind Speed and System Parameter Variability

This paper proposes an Adaptive Robust Control (ARC) strategy for pump-controlled pitch systems in large wind turbines to address challenges in control accuracy and energy efficiency. First, a mathematical model integrating pitch angle dynamics and hydraulic characteristics is established, with pitch angle, pitch angular velocity, and hydraulic cylinder thrust as state variables. Then, an ARC strategy is designed using the backstepping method and incorporating parameter adaptation to handle system nonlinearities and uncertainties. The controller parameters are optimized using Particle Swarm Optimization (PSO) under wind disturbance conditions, and comparative analyses are conducted with traditional PID control. The numerical simulation results show that both controllers achieve similar tracking performance under nominal conditions, with PID achieving a 0.08° maximum error and ARC showing a 0.1° maximum error. However, the ARC strategy demonstrates superior robustness under parameter variations, maintaining tracking errors below 0.15°, while the PID error increases to 1.5°. Physical test bench experiments further validate these findings, with ARC showing significantly better performance during cylinder retraction with 0.1° error compared to PID’s 0.7° error. The proposed control strategy effectively handles both the inherent nonlinearities of the pump-controlled system and external disturbances, providing a practical solution for precise pitch control in large wind turbines while maintaining energy efficiency through the pump-controlled approach.

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Publication Details

Journal
Applied Sciences
Published
2024-11-07
DOI
https://doi.org/10.3390/app142210218
Citations
2
Primary Topic
Hydraulic and Pneumatic Systems
Type
article
Field-Weighted Citation Impact
0.43
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article

Adaptive Robust Control for Pump-Controlled Pitch Systems Facing Wind Speed and System Parameter Variability

Bo Yu, Gexin Chen, Tiangui Zhang, Keyi Liu et al.
2 citations
Applied Sciences
Hydraulic and Pneumatic Systems
0.43
article

Adaptive Robust Control for Pump-Controlled Pitch Systems Facing Wind Speed and System Parameter Variability

Bo Yu, Gexin Chen, Tiangui Zhang, Keyi Liu, Yinping Liu, Lihui Wang, Xuewei Wang, Chao Ai
article en
2 citations

Abstract

This paper proposes an Adaptive Robust Control (ARC) strategy for pump-controlled pitch systems in large wind turbines to address challenges in control accuracy and energy efficiency. First, a mathematical model integrating pitch angle dynamics and hydraulic characteristics is established, with pitch angle, pitch angular velocity, and hydraulic cylinder thrust as state variables. Then, an ARC strategy is designed using the backstepping method and incorporating parameter adaptation to handle system nonlinearities and uncertainties. The controller parameters are optimized using Particle Swarm Optimization (PSO) under wind disturbance conditions, and comparative analyses are conducted with traditional PID control. The numerical simulation results show that both controllers achieve similar tracking performance under nominal conditions, with PID achieving a 0.08° maximum error and ARC showing a 0.1° maximum error. However, the ARC strategy demonstrates superior robustness under parameter variations, maintaining tracking errors below 0.15°, while the PID error increases to 1.5°. Physical test bench experiments further validate these findings, with ARC showing significantly better performance during cylinder retraction with 0.1° error compared to PID’s 0.7° error. The proposed control strategy effectively handles both the inherent nonlinearities of the pump-controlled system and external disturbances, providing a practical solution for precise pitch control in large wind turbines while maintaining energy efficiency through the pump-controlled approach.

Applied SciencesVol. 14(22)
Jilin University (CN), Yanshan University (CN), Xinjiang Institute of Engineering (CN), Shandong Iron and Steel Group (China) (CN), Shougang (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 41%
Hydraulic and Pneumatic Systems
0.43
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