基于T-S模糊模型的风力机系统事件触发控制

王佳伟; 刘亚娟; 宋子秋

doi:10.19805/j.cnki.jcspe.2026.250373

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

基于T-S模糊模型的风力机系统事件触发控制

数字化与智能化 | 更新时间：2026-09-15

- 基于T-S模糊模型的风力机系统事件触发控制
- Event-triggered Control of Wind Turbine System Based on T-S Fuzzy Model
- 动力工程学报 2026年46卷第9期页码：152-161
- 作者机构：
- 作者简介：
  
  王佳伟(2001—),男,山西晋城人,硕士研究生,研究方向为风力机事件触发控制。宋子秋(通信作者),男,讲师,博士,E-mail:quson@ncepu.edu.cn。
- 基金信息：
  
  国家自然科学基金资助项目（62273144）;国家资助博士后研究人员计划B档资助项目（GZB20230208）;中央高校基本科研业务费资助项目（2024MS023）
- DOI：10.19805/j.cnki.jcspe.2026.250373
  中图分类号： TK83
- 纸质出版：2026
- 稿件说明：
移动端阅览
王佳伟, 刘亚娟, 宋子秋. 基于T-S模糊模型的风力机系统事件触发控制[J]. 动力工程学报, 2026, 46(9): 152-161.
王佳伟, 刘亚娟, 宋子秋. 基于T-S模糊模型的风力机系统事件触发控制[J]. 动力工程学报, 2026, 46(9): 152-161. DOI： 10.19805/j.cnki.jcspe.2026.250373.

DOI： 10.19805/j.cnki.jcspe.2026.250373

摘要

针对海上风力机在高频风速扰动和通信资源受限条件下存在的控制效率低与通信负载重的问题，提出了一种基于T-S模糊模型的自适应事件触发控制方法。通过构建不同风速工况下的T-S模糊增量模型，实现对风力机系统非线性动态特性的有效建模。控制器采用状态误差驱动的事件触发机制以降低通信频率。基于Lyapunov稳定性理论，通过求解线性矩阵不等式获得相关增益完成控制器的设计。设计中引入H∞性能指标以提高系统对风扰动影响的抑制能力。仿真结果表明，所设计的控制器能减小阶跃风和湍流风等典型风扰动给系统带来的影响，使风力机功率稳定在一定范围内，同时显著降低系统的通信负载。

Abstract

An adaptive event-triggered control method based on T-S fuzzy model was proposed to address the problems of low control efficiency and heavy communication load of offshore wind turbines under high-frequency wind speed disturbances and limited communication resources. By constructing T-S fuzzy incremental models under different wind speed conditions

the nonlinear dynamic characteristics of wind turbine system were effectively modeled. The controller adopts a state-error-driven event-triggered mechanism to reduce the communication frequency. Based on Lyapunov stability theory

the relevant gains were obtained by solving linear matrix inequalities to complete the controller design. The H∞ performance index was introduced in the design to enhance the suppression capability against wind disturbances in system. Simulation results demonstrate that the designed controller can mitigate the impacts of typical wind disturbances including step wind and turbulent wind on the system

stabilize the output power of the wind turbine within a specified range

and significantly reduce the communication load of system.

关键词

Keywords

references

宋子秋, 余照国, 胡阳, 等. 海上漂浮式风电场高比例并网一次调频控制策略研究[J]. 动力工程学报, 2023, 43(1): 92-101. SONG Ziqiu, YU Zhaoguo, HU Yang, et al. Research on primary frequency regulation control strategy of high-penetration offshore floating wind farm[J]. Journal of Chinese Society of Power Engineering, 2023, 43(1): 92-101.

黄心伟, 柳亦兵, 刘剑韬, 等. 半潜式平台结构尺寸对海上风电机组稳定性的影响研究[J]. 动力工程学报, 2024, 44(12): 1878-1886. HUANG Xinwei, LIU Yibing, LIU Jiantao, et al. Impact of structural dimensions of semi-submersible platform on the stability of offshore wind turbines[J]. Journal of Chinese Society of Power Engineering, 2024, 44(12): 1878-1886.

许昱涵, 吴泽龙, 宋子秋, 等. 基于波浪区间估计与预测的漂浮式风机功率控制方法[J]. 动力工程学报, 2025, 45(5): 706-713. XU Yuhan, WU Zelong, SONG Ziqiu, et al. Power control method for floating offshore wind turbines based on wave interval estimation and prediction[J]. Journal of Chinese Society of Power Engineering, 2025, 45(5): 706-713.

迟永宁, 梁伟, 张占奎, 等. 大规模海上风电输电与并网关键技术研究综述[J]. 中国电机工程学报, 2016, 36(14): 3758-3770. CHI Yongning, LIANG Wei, ZHANG Zhankui, et al. An overview on key technologies regarding power transmission and grid integration of large scale offshore wind power[J]. Proceedings of the CSEE, 2016, 36(14): 3758-3770.

LU Shixiang, GAO Zhiwei, ZHANG Ping, et al. Event-triggered federated learning for fault diagnosis of offshore wind turbines with decentralized data[J]. IEEE Transactions on Automation Science and Engineering, 2024, 21(2): 1271-1283.

温浩远. 基于T-S模糊模型的漂浮式风力发电机组多目标控制策略研究[D]. 北京：华北电力大学(北京), 2025.WEN Haoyuan. Research on multi-objective control strategy for floating wind turbine based on T-S fuzzy model[D]. Beijing：North China Electric Power University, 2025.

张文广, 骆伟健, 孙嘉壕. 双转子风力机气动建模与控制仿真研究[J]. 动力工程学报, 2023, 43(9): 1198-1206. ZHANG Wenguang, LUO Weijian, SUN Jiahao. Research on aerodynamic modeling and control simulation of dual-rotor wind turbine[J]. Journal of Chinese Society of Power Engineering, 2023, 43(9): 1198-1206.

WANG Feng, CHEN Jincheng, CHENG Min, et al. A novel hydraulic transmission solution to large offshore wind turbine: design and control strategy[J]. Ocean Engineering, 2022, 255: 111285.

张艳峰, 杨锡运, 王忻哲. 基于改进无模型自适应控制的漂浮式海上风机转矩-变桨协调控制策略研究[J]. 动力工程学报, 2024, 44(4): 607-615. ZHANG Yanfeng, YANG Xiyun, WANG Xinzhe. Research on torque-pitch coordinated control of floating offshore wind turbines based on improved model-free adaptive control[J]. Journal of Chinese Society of Power Engineering, 2024, 44(4): 607-615.

王会盼, 刘吉臻, 胡阳, 等. 基于预测控制的大惯量风机全工况功率调度跟踪[J]. 电网技术, 2020, 44(7): 2520-2528. WANG Huipan, LIU Jizhen, HU Yang, et al. Power dispatching tracking of large-inertia wind turbine under full operating conditions based on predictive control[J]. Power System Technology, 2020, 44(7): 2520-2528.

EL-BAKLISH S K, EL-BADAWY A A, FRISON G, et al. Nonlinear model predictive pitch control of aero-elastic wind turbine blades[J]. Renewable Energy, 2020, 161: 777-791.

刘娟, 张皓, 王祝萍. 基于自触发的异构多智能体协同输出调节[J]. 自动化学报, 2019, 45(10): 1893-1902. LIU Juan, ZHANG Hao, WANG Zhuping. Cooperative output regulation of heterogeneous multi-agent systems by self-triggered[J]. Acta Automatica Sinica, 2019, 45(10): 1893-1902.

JONKMAN J, BUTTERFIELD S, MUSIAL W, et al. Definition of a 5-MW reference wind turbine for offshore system development[R]. Golden: National Renewable Energy Laboratory, 2009.

VENKAIAH P, SARKAR B K. Hydraulically actuated horizontal axis wind turbine pitch control by model free adaptive controller[J]. Renewable Energy, 2020, 147: 55-68.

宋文静, 谢源, 黄文君, 等. 一种基于改进自抗扰控制器的风电机组变桨距控制策略[J]. 科学技术与工程, 2020, 20(7): 2719-2726. SONG Wenjing, XIE Yuan, HUANG Wenjun, et al. A variable pitch control strategy for wind turbines based on improved active disturbance rejection controller[J]. Science Technology and Engineering, 2020, 20(7): 2719-2726.

夏天, 杨超, 宋进良, 等. 基于动态事件触发复合输出一致性的直流微网电池储能系统分布式控制策略[J]. 电力电容器与无功补偿, 2025, 46(2): 44-52. XIA Tian, YANG Chao, SONG Jinliang, et al. Distributed control strategy for battery energy storage system in DC microgrid based on dynamic event-triggered composite output consistency[J]. Power Capacitor & Reactive Power Compensation, 2025, 46(2): 44-52.

丁瑞森, 杨飞生, 付远超, 等. 混合攻击下基于带宽感知型事件触发机制的负荷频率控制[J]. 中国科学: 信息科学, 2024, 54(12): 2828-2840. DING Ruisen, YANG Feisheng, FU Yuanchao, et al. Load frequency control based on bandwidth-aware event-triggering mechanism under hybrid attacks[J]. Scientia Sinica (Informationis), 2024, 54(12): 2828-2840.

王敏, 孙宗耀, 刘新芝, 等. 基于事件触发策略的受扰非线性系统的预设性能跟踪控制[J]. 控制与决策, 2025, 40(5): 1467-1473. WANG Min, SUN Zongyao, LIU Xinzhi, et al. Event-triggered prescribed performance control for a class of nonlinear system subject to disturbances[J]. Control and Decision, 2025, 40(5): 1467-1473.

PONNARASI L, PANKAJAVALLI P B, LIM Y, et al. Optimization-based event-triggered state estimation algorithm for IoT-based wind turbine systems[J]. IEEE Internet of Things Journal, 2024, 11(6): 9645-9655.

QIAO Siwei, LIU Xinghua, XIAO Gaoxi, et al. Reliable control of wind power systems under frequency-based deception attacks: AMD event-triggered strategy[J]. IEEE Transactions on Reliability, 2025, 74(1): 2027-2040.

YAN Shen, GU Zhou, PARK J H, et al. Adaptive memory-event-triggered static output control of T-S fuzzy wind turbine systems[J]. IEEE Transactions on Fuzzy Systems, 2022, 30(9): 3894-3904.

ZHAO Ya, YANG Xiyun, ZHANG Yanfeng, et al. Event-triggered H-infinity pitch control for floating offshore wind turbines[J]. IEEE Transactions on Sustainable Energy, 2025, 16(2): 1329-1339.

刘亚娟, 孙荷雨, 宋子秋, 等. 降低海面覆冰载荷影响的近海固定式风电机组安全控制[J]. 中国电机工程学报, 2023, 43(16): 6320-6331. LIU Yajuan, SUN Heyu, SONG Ziqiu, et al. Safety control of offshore stationary wind turbine to reduce the influence of ice load on the sea surface[J]. Proceedings of the CSEE, 2023, 43(16): 6320-6331.

JONKMAN J, BUTTERFIELD S, MUSIAL W, et al. Definition of a 5-MW reference wind turbine for offshore system development: NREL/TP-500-38060[S]. Golden: National Renewable Energy Laboratory, 2009.

self-triggered model predictive control for accurate stopping of high-speed trains[J]. Acta Automatica Sinica, 2022, 48(1): 171-181.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于Leckner模型的氨掺烧高水蒸气浓度烟气对燃煤锅炉传热特性的影响分析

基于WOA的循环流化床锅炉SO2排放浓度VMD-Transformer预测模型

基于TDLAS的二维温度场与H2O浓度场重建研究

分形特征对漂浮式风力机仿生平台动态响应的影响

基于全流道冷却集热器的PVT系统热电性能研究