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.
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;
Conference_Titel :
American Control Conference, 1985
Conference_Location :
Boston, MA, USA