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State Estimation Model of Fermentation Process Based on PSO-SVR


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State Estimation Model of Fermentation Process Based on PSO-SVR
XIONG Wei-liXU Bao-guo
School of Communication and Control Engineering,Southern Yangtze University,Wuxi 214122,China
support vector regression state estimation particle swarm optimization fermentation process beta-mannanase
In view of the hardship to get real-time and on-line biological parameters in fermentation process,a soft sensor model based on support vector machines is established for estimating the biological parameters.The complexity and generalization performance of the support vector regression(SVR) model depend on a good setting of the three parameters ε,c,γ.An algorithm called particle swarm optimization(PSO) is applied to optimize the three parameters synchronously.Based on the proposed method,a PSO-SVR model is developed to estimate the products concentration of beta-mannanase for feedstuff.The control results of fermenter show that the state estimation model based on PSO-SVR has good learning accuracy and generalization performance so as to obtain the real-time and on-line estimation for products concentration of beta-mannanase.


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Last Update: 2012-12-19