In the present work, parametric models for the control of bioreactor temperature have been applied. Various order discrete time model parameters were evaluated theoretically and experimentally. Two types of input signals were used as external force to determine Auto Regressive Moving Average with Exogenous (ARMAX) model parameters with Recursive Least Square (RLS) parameter estimation algorithm. The third order ARMAX model is utilized, and compared with the second order one. Ternary and square disturbances are given to the cooling water flow rate which can be chosen as manipulating variable in closed loop cases. System response is monitored continuously and the model parameters are calculated. The models with experimentally identified parameters are compared with ones that their parameters are identified theoretically.
In
the present work, parametric models for the control of bioreactor temperature
have been applied. Various order discrete time model parameters were evaluated
theoretically and experimentally. Two types of input signals were used as
external force to determine Auto Regressive Moving Average with Exogenous (ARMAX)
model parameters with Recursive Least Square (RLS) parameter estimation
algorithm. The third order ARMAX model is utilized, and compared with the
second order one. Ternary and square disturbances are given to the cooling
water flow rate which can be chosen as manipulating variable in closed loop
cases. System response is monitored continuously and the model parameters are
calculated. The models with experimentally identified parameters are compared
with ones that their parameters are identified theoretically.
Primary Language | English |
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Subjects | Structural Biology |
Journal Section | Articles |
Authors | |
Publication Date | January 7, 2017 |
Submission Date | May 4, 2016 |
Published in Issue | Year 2017 Volume: 4 Issue: 1 |