基于奇异摄动模型的风能转换系统H容错保性能控制

姜萍, 李梦瑶, 王培光, 付磊, 张照彦

太阳能学报 ›› 2023, Vol. 44 ›› Issue (9) : 326-333.

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太阳能学报 ›› 2023, Vol. 44 ›› Issue (9) : 326-333. DOI: 10.19912/j.0254-0096.tynxb.2022-0721

基于奇异摄动模型的风能转换系统H容错保性能控制

  • 姜萍, 李梦瑶, 王培光, 付磊, 张照彦
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H FAULT-TOLERANT GUARANTEED COST CONTROL FOR WIND ENERGY CONVERSION SYSTEM BASED ON SINGULAR PERTURBATION MODEL

  • Jiang Ping, Li Mengyao, Wang Peiguang, Fu Lei, Zhang Zhaoyan
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摘要

在风能转换过程中,针对执行器故障、容错控制成本高等问题,设计了H∞最优容错保性能控制器,并基于PI观测器进行了故障诊断。首先,将风电系统中存在的时滞、参数不确定、执行器故障等问题用奇异摄动LPV模型表达;然后,设计PI观测器进行执行器故障重构,并在H∞性能指标和成本性能指标双重约束下,进行凸优化计算,得到最优容错保性能控制律。仿真表明,低风速时,控制器能有效跟踪最优风轮转速,实现最大风能捕获。

Abstract

In the process of wind energy conversion, a H∞ optimal fault-tolerant performance controller was designed to solve the problem of actuator failure and high cost of fault-tolerant control, and a PI observer was proposed to get the fault diagnosis. First, the deficiencies such as time delay, parameter uncertainty and actuator failure in wind power systems are expressed by the singular perturbed linear parameter varying(LPV) model. Second, a PI observer is designed for actuator fault reconstruction, under the dual constraints of H∞ performance index and cost performance index, the feedback gain of the optimal guaranteed cost fault-tolerant control law is wrought out by solving the convex optimization problem. Simulation results show that at low wind speed, the controller can effectively track the optimal rotor speed and achieve the maximum wind energy capture.

关键词

风能 / 奇异摄动系统 / 容错控制 / 鲁棒性 / 保性能控制

Key words

wind power / singularly perturbed systems / fault tolerance / robustness / guaranteed cost control

引用本文

导出引用
姜萍, 李梦瑶, 王培光, 付磊, 张照彦. 基于奇异摄动模型的风能转换系统H容错保性能控制[J]. 太阳能学报. 2023, 44(9): 326-333 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0721
Jiang Ping, Li Mengyao, Wang Peiguang, Fu Lei, Zhang Zhaoyan. H FAULT-TOLERANT GUARANTEED COST CONTROL FOR WIND ENERGY CONVERSION SYSTEM BASED ON SINGULAR PERTURBATION MODEL[J]. Acta Energiae Solaris Sinica. 2023, 44(9): 326-333 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0721
中图分类号: TM614   

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基金

中央引导地方科技发展基金(226Z2103G); 河北省自然科学基金(A2020201021); 国家自然科学基金(62103126)

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