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  • 标题:Detection and diagnosis of model-plant mismatch in MIMO systems using plant-model ratio
  • 本地全文:下载
  • 作者:Suraj Yerramilli ; Arun K. Tangirala
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2016
  • 卷号:49
  • 期号:1
  • 页码:266-271
  • DOI:10.1016/j.ifacol.2016.03.064
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe performance of any model-based controller depends on the quality of the model and hence on the model-plant mismatch (MPM). Model maintenance and correction is necessary to achieve desired performance. However, a complete re-identification of the model is usually a costly exercise. Therefore, it would be highly desirable to detect the precise location of the mismatch and update only those parts. The recently introduced plant-model ratio (PMR) was found to be effective in detecting and diagnosing MPM from closed loop operation data for SISO systems. The PMR facilitates a unique identification of the source of mismatch - namely gain, dynamics and delay mismatches. However, direct application of PMR to MIMO systems is a challenge due to the presence of interactions between the various input-output channels. In this paper, the PMR approach is extended to MIMO control systems. It is assumed that the control loop is driven through broadband excitation in the set-points. The key step in the proposed methodology involves decoupling interactions using partial cross-spectral density. The proposed methodology is able to detect the input-output channels with significant mismatch as well as identify the source of mismatch within these channels. The efficacy of this method is demonstrated through two simulation case studies.
  • 关键词:Keywordsmodel-plant mismatchMIMOfrequency domainplant-model ratiopartial cross-spectral densitymodel-based control
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