DocumentCode :
486208
Title :
Uncertainty in Sampled Systems
Author :
Rohrs, Charles E. ; Stein, Gunter ; Astrom, Karl J.
Author_Institution :
Tellabs Research Laboratory, South Bend, IN; Department of Electrical Engineering, University of Notre Dame, Notre Dame, Indiana 46556.
fYear :
1985
fDate :
19-21 June 1985
Firstpage :
95
Lastpage :
97
Abstract :
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.
Keywords :
Adaptive algorithm; Adaptive control; Adaptive systems; Filters; Frequency response; Programmable control; Sampled data systems; Sampling methods; Stability; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 1985
Conference_Location :
Boston, MA, USA
Type :
conf
Filename :
4788586
Link To Document :
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