The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Uncertainty in Sampled Systems

På svenska

Author

Summary, in English

The recently obtained evidence of the need for a positive real element in an adaptive system leaves us with a disturbing gap in adaptive control theory. It is a fact that in some applications adaptive controllers are performing well in practice. How can these systems behave well in practical situations which must contain modeling error? This paper introduces a preliminary result which indicates that it may be possible to maintain the needed positive real system in the presence of modeling error. The result shows that if a continuous-time system with large high frequency uncertainty is treated appropriately with antialiasing filters and sampled slowly enough, the resulting discrete-time system may contain very little uncertainty. With small enough uncertainty in the plant, a positive real system in the adaptive loop is possible

Publishing year

1985

Language

English

Document type

Conference paper

Topic

  • Control Engineering

Keywords

  • Adaptive algorithm
  • Adaptive control
  • Adaptive systems
  • Filters
  • Frequency response
  • Programmable control
  • Sampled data systems
  • Sampling methods
  • Stability Uncertainty

Conference name

American Control Conference, 1985

Conference date

1985-06-19 - 1985-06-21

Conference place

Boston, Massachusetts, United States

Status

Published