Modified ADRC for Inertial Stabilized Platform With Corrected Disturbance Compensation and Improved Speed Observer

Qu, Junhai; Xia, Yuanqing; Shi, Yanyun; Cao, Jingjing; Wang, Haiwen; Meng, Yunxia

doi:10.1109/access.2020.3020143

Cited by 8 publications

(1 citation statement)

References 29 publications

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“…Several studies have demonstrated the successful application of ADRC in different control systems with impressive control performance [6][7][8]. Additionally, combining ADRC with the inertia control method has resulted in significant improvements in system frequency fluctuation amplitude and settling time [9][10].…”

Section: Introductionmentioning

confidence: 99%

Wind Power Virtual Inertia Frequency Modulation Control Based on Intelligent Swarm Auto-Disturbance Rejection

Li,

Yao

et al. 2024

Advances in Transdisciplinary Engineering

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This paper proposes a wind power virtual inertia control strategy based on the intelligent bee colony active disturbance rejection controller (ABC-ADRC). The proposed control method aims to improve the anti-interference capability of the virtual inertia control system and solve the challenge of tuning the parameters of the active disturbance rejection control (ADRC).The control strategy is developed based on the system frequency dynamic response equation. An active disturbance rejection controller is designed using a nonlinear feedback control law and an extended state observer. This controller aims to enhance the system’s ability to reject disturbances. However, tuning the parameters of the ADRC can be difficult. To address this issue, an ABC algorithm based on nectar collection behavior is proposed to iteratively optimize the ADRC parameters. The proposed control method is verified through simulations using Matlab/Simulink. The results demonstrate that the ABC-ADRC control strategy is more effective compared to traditional algorithms. It successfully controls the rotor speed to adjust the frequency of the power grid system, achieves power sharing, and eliminates adaptive noise. Furthermore, this method reduces the complexity of parameter settings, improves anti-interference ability, and enhances the robustness of the system.

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