Mixed Unscented Kalman Filter and differential evolution for parameter identification
This paper presents parameters estimation techniques for coupled industrial tanks using the mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) method. UKF have known to be a typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical syst...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Trans Tech Publications
2013
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/27209/ http://irep.iium.edu.my/27209/ http://irep.iium.edu.my/27209/ http://irep.iium.edu.my/27209/1/AMM.256-259.2347_Journal.pdf |
| Summary: | This paper presents parameters estimation techniques for coupled industrial tanks using
the mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) method. UKF have
known to be a typical estimation technique used to estimate the state vectors and parameters of
nonlinear dynamical systems and DE is one of the most powerful stochastic real-parameter
optimization algorithms. Meanwhile, liquid tank systems play important role in industrial
application such as in food processing, beverage, dairy, filtration, effluent treatment, pharmaceutical
industry, water purification system, industrial chemical processing and spray coating. The aim is to
model the coupled tank system using mixed UKF and DE method to estimate the parameters of the
tank. First, a non-linear mathematical model is developed. Next, its parameters are identified using
mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) based on the experimental
data. DE algorithm is integrated into the UKF algorithm to optimize the Kalman gain obtained. The
obtained results demonstrate good performances. |
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