International Journal of Engineering and Manufacturing(IJEM)
ISSN: 2305-3631 (Print), ISSN: 2306-5982 (Online)
Published By: MECS Press
IJEM Vol.11, No.5, Oct. 2021
Parametric optimization of Liquid Flow Process by ANOVA Optimized DE, PSO & GA Algorithms
Full Text (PDF, 706KB), PP.14-24
Control of liquid level & flow are the most interest domain in process control industry. Generally process parameter of the liquid flow system is varied frequently during the operation. So the selection of the level of process parameters i.e. input variables seems to be important for achieving the optimum flow rate. In the present work focus is given on the identification of the proper combination of the input parameters in liquid flow rate process. Flow sensor output, pipe diameter, liquid conductivity & viscosity have been taken as input parameter; flow rate obtained from test is taken as response parameter. Till now several researchers have been performed various optimization methods for optimized the parameters of the process plant. But still computational time & convergence speed of the applied optimization techniques for the modelling of the nonlinear process system is still an open challenge for the modern research. In this research we proposed three evolutionary algorithms are used to optimize the process parameters of the nonlinear model implemented by ANOVA to mitigate the unbalance, convergence speed and reduce the total computational time. Overall research performed into three stage, in first phase nonlinear equation ANOVA has been used for mathematical model for the process, In second stage three evolutionary algorithms: GA, PSO & DE are applied for parametric optimization of liquid flow process to maximize the response parameter & in last phase comparative study performed on simulated results based on confirmed test & validated our proposed methodology.
Cite This Paper
Pijush Dutta, Madhurima Majumder, Asok Kumar, " Parametric optimization of Liquid Flow Process by ANOVA Optimized DE, PSO & GA Algorithms ", International Journal of Engineering and Manufacturing (IJEM), Vol.11, No.5, pp. 14-24, 2021. DOI: 10.5815/ijem.2021.05.02
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