Predictive Kalman filter-based fault estimator and control for sampled-data linear time-varying systems

Jason Sheng Hong Tsai, Chao Lung Wei, Shu Mei Guo, Leang San Shieh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The universal state-space adaptive observer-based fault diagnosis/estimator and the high-gain property tracker for sampled-data linear slowly time-varying system with unanticipated decay factors in actuators/system states are proposed in this paper. An improved Kalman filter-based adaptive observer is proposed in this paper to achieve better estimation-based performance recovery than the conventional one. A residual generation scheme and a mechanism for auto-tuning switched gain is presented, so that the proposed methodology is applicable for the fault detection and diagnosis (FDD) for actuator and state failures to yield high tracking performance recovery. For practical implementation, this paper also takes advantage of the merit of digital redesign methodology to convert a theoretically well-designed analog controller/observer with a high-gain property into its corresponding low-gain digital controller/observer without possibly losing the high tracking/estimation as well as FDD performance recovery.

Original languageEnglish
Title of host publicationISIE 2010 - 2010 IEEE International Symposium on Industrial Electronics
Pages292-297
Number of pages6
DOIs
Publication statusPublished - 2010 Dec 28
Event2010 IEEE International Symposium on Industrial Electronics, ISIE 2010 - Bari, Italy
Duration: 2010 Jul 42010 Jul 7

Publication series

NameIEEE International Symposium on Industrial Electronics

Other

Other2010 IEEE International Symposium on Industrial Electronics, ISIE 2010
CountryItaly
CityBari
Period10-07-0410-07-07

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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