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  • 标题:Modulation-Function-Based Finite-Horizon Sensor Fault Detection for Salient-Pole PMSM using Parity-Space Residuals
  • 本地全文:下载
  • 作者:Benjamin Jahn ; Yuri A.W. Shardt
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:7
  • 页码:61-66
  • DOI:10.1016/j.ifacol.2021.08.335
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractAn online model-based fault detection and isolation method for salient-pole permanent magnet synchronous motors over a finite horizon is proposed. The proposed approach combines parity-space-based residual generation and modulation-function-based filtering. Given the polynomial model equations, the unknown variables(i.e.the states, unmeasured inputs) are eliminated resulting in analytic redundancy relations used for residual generation. Furthermore, in order to avoid needing the derivatives of measured signals required by such analytic redundancy relations, a modulation-function-based evaluation is proposed. This results in a finite-horizon filtered version of the original residual. The fault detection and isolation method is demonstrated using simulation of various fault scenarios for a speed controlled salient motor showing the effectiveness of the presented approach.
  • 关键词:KeywordsPermanent Magnet Synchronous MotorSensor Fault DetectionAnalytic Redundancy RelationsModulation Functions
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