Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control

This paper focuses on design of a glucose concentration control system based on nonlinear model plant of E. coli MC4110 fed-batch cultivation process. Due to significant time delay in real time glucose concentration measurement, a correction is proposed in glucose concentration measurement and a Smi...

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Main Authors: Tsonyo Slavov, Olympia Roeva
Format: Article
Language:English
Published: Bulgarian Academy of Sciences 2011-07-01
Series:International Journal Bioautomation
Subjects:
Online Access:http://www.clbme.bas.bg/bioautomation/2011/vol_15.2/files/15.2_03.pdf
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spelling doaj-8b952e1031954bb097c700b57044e6d42020-11-25T02:50:39ZengBulgarian Academy of SciencesInternational Journal Bioautomation1314-19021314-23212011-07-01152101114Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration ControlTsonyo SlavovOlympia RoevaThis paper focuses on design of a glucose concentration control system based on nonlinear model plant of E. coli MC4110 fed-batch cultivation process. Due to significant time delay in real time glucose concentration measurement, a correction is proposed in glucose concentration measurement and a Smith predictor (SP) control structure based on universal PID controller is designed. To reduce the influence of model error in SP structure the estimate of measured glucose concentration is used. For the aim an extended Kalman filter (EKF) is designed. To achieve good closed-loop system performance genetic algorithm (GA) based optimal controller tuning procedure is applied. A standard binary encoding GA is applied. The GA parameters and operators are specified for the considered here problem. As a result the optimal PID controller settings are obtained. The simulation experiments of the control systems based on SP with EKF and without EKF are performed. The results show that the control system based on SP with EKF has a better performance than the one without EKF. For a short time the controller sets the control variable and maintains it at the desired set point during the cultivation process. As a result, a high biomass concentration of 48.3 g·l-1 is obtained at the end of the process.http://www.clbme.bas.bg/bioautomation/2011/vol_15.2/files/15.2_03.pdfE. coli cultivationSmith predictorPID controller tuningGenetic algorithmExtended Kalman filter
collection DOAJ
language English
format Article
sources DOAJ
author Tsonyo Slavov
Olympia Roeva
spellingShingle Tsonyo Slavov
Olympia Roeva
Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control
International Journal Bioautomation
E. coli cultivation
Smith predictor
PID controller tuning
Genetic algorithm
Extended Kalman filter
author_facet Tsonyo Slavov
Olympia Roeva
author_sort Tsonyo Slavov
title Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control
title_short Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control
title_full Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control
title_fullStr Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control
title_full_unstemmed Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control
title_sort genetic algorithm tuning of pid controller in smith predictor for glucose concentration control
publisher Bulgarian Academy of Sciences
series International Journal Bioautomation
issn 1314-1902
1314-2321
publishDate 2011-07-01
description This paper focuses on design of a glucose concentration control system based on nonlinear model plant of E. coli MC4110 fed-batch cultivation process. Due to significant time delay in real time glucose concentration measurement, a correction is proposed in glucose concentration measurement and a Smith predictor (SP) control structure based on universal PID controller is designed. To reduce the influence of model error in SP structure the estimate of measured glucose concentration is used. For the aim an extended Kalman filter (EKF) is designed. To achieve good closed-loop system performance genetic algorithm (GA) based optimal controller tuning procedure is applied. A standard binary encoding GA is applied. The GA parameters and operators are specified for the considered here problem. As a result the optimal PID controller settings are obtained. The simulation experiments of the control systems based on SP with EKF and without EKF are performed. The results show that the control system based on SP with EKF has a better performance than the one without EKF. For a short time the controller sets the control variable and maintains it at the desired set point during the cultivation process. As a result, a high biomass concentration of 48.3 g·l-1 is obtained at the end of the process.
topic E. coli cultivation
Smith predictor
PID controller tuning
Genetic algorithm
Extended Kalman filter
url http://www.clbme.bas.bg/bioautomation/2011/vol_15.2/files/15.2_03.pdf
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