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A function state space approach to robust tracking for sampled-data systems

  • Yutaka Yamamoto
Conference paper
  • 255 Downloads
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 183)

Abstract

It is well known that tracking to continuous-time signals by sampled-data systems presents various difficulties. For example, the usual discrete-time model is not suitable for describing intersample ripples. In order to adequately handle this problem we need a framework that explicitly contains the intersample behavior in the model. This paper presents an infinite-dimensional yet time-invariant discrete-time model which contains the full intersample behavior as information in the state. This makes it possible to clearly understand the intersample as a result of a mismatch between the intersample tracking signal and the system zero-directional vector. This leads to an internal model principle for sampled-data systems, and some nonclassical feature arising from the interplay of digital and continuous-time behavior.

Keywords

Loop Transfer Function Nonclassical Feature Internal Model Principle Digital Compensator Function Space Method 
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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Copyright information

© Springer-Verlag 1992

Authors and Affiliations

  • Yutaka Yamamoto

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