Author/Authors :
Yucai Zhu، نويسنده ,
Title Of Article :
Multivariable process identification for mpc: the asymptotic method and its applications
Latin Abstract :
In this work we will introduce the asymptotic method (ASYM) of identification and provide two case
studies. The ASYM was developed for multivariable process identification for model based control. The
method calculates time de main parametric models using frequency domain criterion. Fundamental
problems, such as test signal design for control, model order/structure selection, parameter estimation and
model error quantification, are solved in a systematic manner. The method can supply not only input/
output model and unmeasured disturbance model which are asymptotic maximum likelihood estimates,
but also the upper bound matrix for the model errors that can be used for model validation and robustness
analysis. To demonstrate the use of the method for model predictive control (MPC), the identification of a
Shell benchmark process (a simulated distillation column) and an industrial application to a crude unit
atmospheric tower will be presented.
NaturalLanguageKeyword :
multivariable process , Test design , Identification , Order selection , parameter estimation , modelvalidation , model predictive mntrol , distillation columns
JournalTitle :
Studia Iranica
