为消除风电叶片静力加载试验中多节点间加载力交联耦合造成的载荷振荡影响,提出一种基于智能优化算法自整定参数的比例-积分-微分（PID）解耦控制策略。首先,建立多节点加载力与挠度变化之间的数学模型,以71.5 m叶片无算法控制加载为例揭示交联耦合响应特性。其次,结合变速积分与不完全微分的PID控制策略,提出一种改进天牛须搜索算法,用于非线性加载过程中PID参数的在线自整定。最后,将提出的控制策略应用于110.5 m风电叶片七节点静载现场试验,结果表明该控制策略能有效降低多节点交联耦合,满足加载力协同控制要求,实现大型叶片静载试验的平稳加载。
Abstract
To eliminate the effect of load oscillation caused by cross-link coupling of loading force between multiple nodes in the static loading test of wind turbine blades, a proportional-integral-derivative（PID） decoupling control strategy based on an intelligent optimization algorithm with self-tuning parameters is proposed. Firstly, the mathematical model, between multi-node loading force and the deflection variation of multiple nodes is established, and the algorithm-free control loading of a 71.5 m blade is taken as an example to reveal the cross-link coupling response characteristics. Secondly, combining the variable speed integral and incomplete differential PID control strategy, an improved Beetle Antennae Search algorithm is proposed for the online self-tuning of PID parameters in the nonlinear loading process. Finally, the proposed control strategy is applied to a seven-node static load proof test of 110.5 m wind turbine blades. The results show that the control strategy can effectively reduce the multi-node cross-link coupling, meet the requirements of coordination control of loading force, and realize stable loading of large blade static loading test.
关键词
风力机 /
叶片 /
载荷控制 /
解耦策略 /
静力加载试验 /
改进天牛须搜索算法
Key words
wind turbines /
blades /
load control /
decoupling control strategy /
static loading test /
improved beetle antennae search algorithm
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] JUNG C, SCHINDLER D.Efficiency and effectiveness of global onshore wind energy utilization[J]. Energy conversion and management, 2023, 280: 116788.
[2] IEC 61400-23:2014, Wind turbines-Part 23: full-scales tructural testing of rotor blades[S].
[3] DNVGL-ST-0376, Rotor blades for wind turbines[S].
[4] 张磊安, 黄雪梅. 风电叶片全尺寸静力试验加载力协调控制算法[J]. 太阳能学报, 2015, 36(6): 1418-1422.
ZHANG L A, HUANG X M.Loading coordination control algorithm of full-scale static test for wind turbine blade[J]. Acta energiae solaris sinica, 2015, 36(6):1418-1422.
[5] 谢林坡. 基于LabVIEW的多点协调静力加载控制系统[D]. 大连: 大连理工大学, 2017.
XIE L P.Multi-point coordinated static loading control system based on LabVIEW[D]. Dalian: Dalian University of Technology, 2017.
[6] 段连国. 面向大展弦比机翼静力试验的加载机构研究与分析[D]. 秦皇岛: 燕山大学, 2015.
DUAN L G.Research and analysis of loading mechanism for static test of high aspect ratio wing[D]. Qinhuangdao: Yanshan University, 2015.
[7] ZUO D Q, QIAN L X, YANG T E, et al.Coupling leveling control based on fuzzy PID for synchronous loading system of load-bearing test bed[J]. Chinese journal of electronics, 2017, 26(6): 1206-1212.
[8] WANG Z H, LI D S, SHEN L H, et al.Collaborative force and shape control for large composite fuselage panels assembly[J]. Chinese journal of aeronautics, 2023, 36(7): 213-225.
[9] 乌建中. 风电叶片全尺寸结构测试理论基础、系统设计和试验方法[M]. 上海: 同济大学出版社, 2021: 48-56.
WU J Z.Full-scale structural testing theoretical basis, system design and experimental method of wind turbine blades[M]. Shanghai: Tongji University Press, 2021: 48-56.
[10] 同济大学航空航天与力学学院基础力学教学研究部. 材料力学[M]. 上海: 同济大学出版社, 2015: 154-172.
Department of Basic Mechanics Teaching and Research, School of Aerospace and Mechanics, Tongji University. Mechanics of materials[M]. Shanghai: Tongji Press, 2015: 154-172.
[11] 刘常海, 胡敏, 杨庆俊, 等. 波浪能发电半物理仿真试验技术研究[J]. 机械工程学报, 2021, 57(10): 286-296.
LIU C H, HU M, YANG Q J, et al.Hardware-in-the-loop simulation technology of wave power generation[J]. Journal of mechanical engineering, 2021, 57(10): 286-296.
[12] 许景辉, 王雷, 谭小强, 等. 基于SOA优化PID控制参数的智能灌溉控制策略研究[J]. 农业机械学报, 2020, 51(4): 261-267.
XU J H, WANG L, TAN X Q, et al.Application of PID control based on SOA optimization in intelligent irrigation system[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(4): 261-267.
[13] JIANG X Y, LI S.BAS: beetle antennae search algorithm for optimization problems[J]. International journal of robotics and control, 2018, 1(1): 1.
[14] HE W B, LIN C T, WU T A, et al.An improved beetle antennae search algorithm with Lévy flight and its application in micro-laser assisted turning[J]. Advanced engineering informatics, 2022, 54: 101732.
[15] TRIPATHI S M, MISHRA A, PANDEY A K.High performance speed tracking of CSI-fed SCIM drive employing a variable-gain proportional-integral (VGPI) speed controller[J]. Journal of electrical systems and information technology, 2018, 5(3): 635-652.
[16] DANG X J, ZHAO X A, DANG C, et al.Incomplete differentiation-based improved adaptive backstepping integral sliding mode control for position control of hydraulic system[J]. ISA transactions, 2021, 109: 199-217.
[17] RAO C S, SANTOSH S, V D R. Tuning optimal PID controllers for open loop unstable first order plus time delay systems by minimizing ITAE criterion[J]. IFAC-PapersOnLine, 2020, 53(1): 123-128.
[18] 陶立壮, 田德, 唐世泽, 等. 基于遗传算法的海上风电机组齿轮箱体积优化[J]. 太阳能学报, 2021, 42(11): 234-239.
TAO L Z, TIAN D, TANG S Z, et al.Volume optimization of offshore wind turbine gearbox based on genetic algorithms[J]. Acta energiae solaris sinica, 2021, 42(11): 234-239.
[19] 陈际, 袁守利, 刘志恩. 基于BAS改进PSO算法对PEMFC温度的控制[J]. 太阳能学报, 2023, 44(5): 67-73.
CHEN J, YUAN S L, LIU Z E.Temperature control of PEMFC based on BAS improved PSO algorithm[J]. Acta energiae solaris sinica, 2023, 44(5): 67-73.
[20] 吉建华, 苗长云, 李现国, 等. 基于PSO带式输送机PID控制器参数智能整定的适应度函数设计[J]. 机械工程学报, 2023, 59(22): 444-456.
JI J H, MIAO C Y, LI X G, et al.Fitness function design based on intelligent tuning of PID controller parameters of PSO belt conveyor[J]. Journal of mechanical engineering, 2023, 59(22): 444-456.
基金
山东省自然科学基金面上项目（ZR2024ME003; ZR2024ME250）
PDF(2833 KB)
