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Advanced control with parameter estimation of batch transesterification reactor

DSpace at IIT Bombay

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Title Advanced control with parameter estimation of batch transesterification reactor
 
Creator KERN, R
SHASTRI, Y
 
Subject MODEL-PREDICTIVE CONTROL
BIODIESEL PRODUCTION
ADAPTIVE-CONTROL
TEMPERATURE
DYNAMICS
KINETICS
OIL
Transesterification
Optimal control
Nonlinear model predictive control
Parameter estimation
 
Description The objective of this work is to enhance the economic performance of a batch transesterification reactor producing biodiesel by implementing advanced, model based control strategies. To achieve this goal, a dynamic model of the batch reactor system is first developed by considering reaction kinetics, mass balances and heat balances. The possible plant-model mismatch due to inaccurate or uncertain model parameter values can adversely affect model based control strategies. Therefore, an evolutionary algorithm to estimate the uncertain parameters is proposed. It is shown that the system is not observable with the available measurements, and hence a closed loop model predictive control cannot be implemented on a real system. Therefore, the productivity of the reactor is increased by first solving an open-loop optimal control problem. The objective function for this purpose optimizes the concentration of biodiesel, the batch time and the heating and cooling rates to the reactor. Subsequently, a closed-loop nonlinear model predictive control strategy is presented in order to take disturbances and model uncertainties into account. The controller, designed with a reduced model, tracks an offline determined set-point reactor temperature trajectory by manipulating the heating and cooling mass flows to the reactor. Several operational scenarios are simulated and the results are discussed in view of a real application. With the proposed optimization and control strategy and no parameter mismatch, a revenue of 2.76 $ min(-1) can be achieved from the batch reactor. Even with a minor parameter mismatch, the revenue is still 2.01 $ min(-1). While these values are comparable to those reported in the literature, this work also accounts for the cost of energy. Moreover, this approach results in a control strategy that can be implemented on a real system with limited online measurements. (C) 2015 Elsevier Ltd. All rights reserved.
 
Publisher ELSEVIER SCI LTD
 
Date 2016-01-15T04:26:03Z
2016-01-15T04:26:03Z
2015
 
Type Article
 
Identifier JOURNAL OF PROCESS CONTROL, 33,127-139
0959-1524
1873-2771
http://dx.doi.org/10.1016/j.jprocont.2015.06.006
http://dspace.library.iitb.ac.in/jspui/handle/100/17753
 
Language en