Optimizing Thermoacoustic Characterization Experiments for Identifiability Improves Both Parameter Estimation Accuracy and Closed-Loop Controller Robustness Guarantees

Optimizing Thermoacoustic Characterization Experiments for Identifiability Improves Both Parameter Estimation Accuracy and Closed-Loop Controller Robustness Guarantees
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优化热声表征实验以提高可识别性,提高参数估计精度和闭环控制器鲁棒性保证

DOI:
10.1080/00102202.2020.1858818
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发表时间:
2021
影响因子:
1.9
通讯作者:
Fathy, Hosam
Fathy, Hosam
中科院分区:
工程技术4区
文献类型:
--
作者:
Chen, Xiaoling;O’Connor, Jacqueline;Fathy, Hosam

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本文探讨了在何种程度上优化的Rijke管实验可以提高热声模型参数估计的准确性,从而促进鲁棒稳定性控制。我们使用一维热声模型来描述Rijke管中的燃烧动力学。该模型包含两个未知的参数,涉及速度扰动的热释放率振荡,即,一个时间延迟和放大因子。这些参数是从实验中估计的,其中系统输入是来自扬声器的声学激励,输出是由麦克风捕获的压力响应。我们的工作是基于这样的见解,即优化实验的设计,以获得更高的Fisher可识别性,从而获得更准确的参数估计。本文的新目标是在实验室中使用火焰驱动的Rijke管设置应用这种见解。为了比较的目的,我们进行了一个基准实验与宽带啁啾信号作为激励输入。接下来,我们在两个针对Fisher可识别性优化的频率下激发Rijke管。两个实验的重复表明,最优实验实现参数估计的不确定性至少比基准小一个数量级。具有较小的参数估计的不确定性,LQG控制器的设计,以衰减燃烧不稳定性是能够实现更强的鲁棒性保证,量化的闭环结构奇异值,占参数估计的不确定性。
This article examines the degree to which optimizing a Rijke tube experiment can improve the accuracy of thermoacoustic model parameter estimation, thereby facilitating robust stability control. We use a one-dimensional thermoacoustic model to describe the combustion dynamics in a Rijke tube. This model contains two unknown parameters that relate velocity perturbations to heat release rate oscillations, namely, a time delayand amplification factor. The parameters are estimated from experiments where the system input is the acoustic excitation from a loudspeaker and the output is the pressure response captured by a microphone. Our work is grounded in the insight that optimizing an experiment’s design for higher Fisher identifiability leads to more accurate parameter estimates. The novel goal of this paper is to apply this insight in the laboratory using a flame-driven Rijke tube setup. For comparison purposes, we conduct a benchmark experiment with a broadband chirp signal as the excitation input. Next, we excite the Rijke tube at two frequencies optimized for Fisher identifiability. Repeats of both experiments show that the optimal experiment achieves parameter estimates with uncertainties at least one order of magnitude smaller than the benchmark. With smaller parameter estimate uncertainties, an LQG controller designed to attenuate combustion instabilities is able to achieve stronger robustness guarantees, quantified in terms of closed-loop structured singular values that account for parameter estimation uncertainty.
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