Multi-model LPV approach to CSTR system identification with stochastic scheduling variable
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Authors
Wei, J.
Yin, YanYan
Liu, F.
Date
2016Type
Conference Paper
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Wei, J. and Yin, Y. and Liu, F. 2016. Multi-model LPV approach to CSTR system identification with stochastic scheduling variable, pp. 303-307.
Source Title
Proceedings - 2015 Chinese Automation Congress, CAC 2015
ISBN
School
Department of Mathematics and Statistics
Collection
Abstract
© 2015 IEEE.The problem of CSTR system identification is studied with a stochastic scheduling parameter. Multi-model approach is used to describe non-linear process, in which, each linear parameter system is represented by a ARX model. An expectation maximization (EM) algorithm is used for the identification of parameters which are unknown. Furthermore, scheduling variable corresponds to the operating conditions of the nonlinear process is considered as a stochastic parameter, which follows a Markov jump process.
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