Author/Authors
Kenya Murakami and Dale E. Seborg، نويسنده ,
DocumentNumber
1384341
Title Of Article
Constrained parameter estimation with applications to blending operations
شماره ركورد
11583
Latin Abstract
The classical least squares approach to parameter estimation for dynamic models ignores a priori information about the feasible
values of the estimated parameters. But in many practical problems, such information is available in the form of upper and lower
limits. In this paper, two alternative techniques are evaluated for this important class of constrained parameter estimation problems
for dynamic systems. Simulation results for two blending problems illustrate that more accurate parameter estimates and better
predictions can be obtained by using a quadratic programming approach.
From Page
195
NaturalLanguageKeyword
Inequality constraints , Blending systems , Least squares , Quadratic programming , Constrained parameter estimation
JournalTitle
Studia Iranica
To Page
202
To Page
202
Link To Document