ISSN:
1573-2878
Keywords:
learning
;
estimation
;
monitoring
;
industrial processes
;
kernel function
;
passive strategy
;
stochastic approximations
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract A class of estimation/learning algorithms using stochastic approximation in conjunction with two kernel functions is developed. This algorithm is recursive in form and uses known nominal values and other observed quantities. Its convergence analysis is carried out; the rate of convergence is also evaluated. Applications to a nonlinear chemical engineering system are examined through simulation study. The estimates obtained will be useful in process operation and control, and in on-line monitoring and fault detection.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1004622313930
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