An averaging analysis of discrete-time indirect adaptive controlAn averaging analysis of indirect, discrete-time, adaptive control systems is presented. The analysis results in a signal-dependent stability condition and accounts for unmodeled plant dynamics as well as exogenous disturbances. This analysis is applied to two discrete-time adaptive algorithms: an unnormalized gradient algorithm and a recursive least-squares (RLS) algorithm with resetting. Since linearization and averaging are used for the gradient analysis, a local stability result valid for small adaptation gains is found. For RLS with resetting, the assumption is that there is a long time between resets. The results for the two algorithms are virtually identical, emphasizing their similarities in adaptive control.
Document ID
19880067264
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Phillips, Stephen M. (Stanford Univ. CA, United States)
Kosut, Robert L. (Stanford Univ. CA, United States)
Franklin, Gene F. (Stanford University CA, United States)