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State Observer Implementation via Microcomputers with Applications

  • Naresh K. Sinha
Chapter
Part of the International Series on Microprocessor-Based Systems Engineering book series (ISCA, volume 1)

Abstract

The microcomputer implementation of a Luenberger-type state observer for dynamic systems is discussed. For the linear case two types of implementations are considered, (a) when a discrete-time model is used, and (b) when the block-pulse function approach is utilized. Since the observations are invariably contaminated with noise, the former approach must include filtering the outputs before applying to the observer. On the other hand, the latter approach was found suitable even without a filter for a small amount of noise. Extension to the more general case of nonlinear systems is also discussed. The Luenberger-type observer can still be used, but the observer gains may have to be adjusted in an adaptive manner. Some results of simulation as well as a brief desscription of the hardware and the software are included.

Keywords

Sampling Interval Extended Kalman Filter State Observer Gain Matrix Observer Gain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© D. Reidel Publishing Company 1983

Authors and Affiliations

  • Naresh K. Sinha
    • 1
  1. 1.Department of Electrical and Computer EngineeringMcMaster UniversityHamiltonCanada

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