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
中科院分区:
文献类型:
--
作者:
Chen, Xiaoling;O’Connor, Jacqueline;Fathy, Hosam
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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影响因子:
1.9
作者:
S. Murugappan;Shree Krishna Acharya;D. Allgood;S. Park;A. Annaswamy;A. Ghoniem
通讯作者:
S. Murugappan;Shree Krishna Acharya;D. Allgood;S. Park;A. Annaswamy;A. Ghoniem
DOI:
--
发表时间:
2019
期刊:
American Controls Conference
影响因子:
--
作者:
Chen, Xiaoling;Dillen, Evan;Fathy, Hosam;O'Connor, Jacqueline
通讯作者:
O'Connor, Jacqueline
DOI:
--
发表时间:
2011
期刊:
影响因子:
--
作者:
F. Selimefendigil;W. Polifke
通讯作者:
W. Polifke
影响因子:
3.7
作者:
L. Magri;M. Juniper
通讯作者:
M. Juniper
DOI:
--
发表时间:
2014
期刊:
影响因子:
--
作者:
M. Bauerheim;A. Ndiaye;P. Constantine;G. Iaccarino;S. Moreau;F. Nicoud
通讯作者:
F. Nicoud