ISSN:
1573-2754
Keywords:
system identification
;
damped least square
;
recursive algorithm
;
convergence
;
stability
;
O231
;
O241
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
,
Mathematics
,
Physics
Notes:
Abstract The recursive least square is widely used in parameter identification. But it is easy to bring about the phenomena of parameters burst-off. A convergence analysis of a more stable identification algorithm-recursive damped least square is proposed. This is done by normalizing the measurement vector entering into the identification algorithm. It is shown that the parametric distance converges to a zero mean random variable. It is also shown that under persistent excitation condition, the condition number of the adaptation gain matrix is bounded, and the variance of the parametric distance is bounded.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF02458525
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