Control of Input Multiplicity Process (Bioreactor) using Fuzzy logic Techniques

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2019 by IJETT Journal
Volume-67 Issue-5
Year of Publication : 2019
Authors : Ballekallu Chinna Eranna , Daniel Tadesse Abebe , Alemayu Chaufamo
DOI :  10.14445/22315381/IJETT-V67I5P215

Citation 

MLA Style: Ballekallu Chinna Eranna , Daniel Tadesse Abebe , Alemayu Chaufamo "Control of Input Multiplicity Process (Bioreactor) using Fuzzy logic Techniques" International Journal of Engineering Trends and Technology 67.5 (2019):98-103.

APA Style: Ballekallu Chinna Eranna , Daniel Tadesse Abebe , Alemayu Chaufamo (2019). Control of Input Multiplicity Process (Bioreactor) using Fuzzy logic Techniques International Journal of Engineering Trends and Technology,67(5),98-103.

Abstract
In the present work, a Fuzzy logic controller is analyzed to a continuous bioreactor which exhibits input multiplicities in dilution rate on productivity. i.e., two values of dilution rate will give the same value of productivity. The Performance of proposed Fuzzy logic controller and conventional PI controller has been evaluated near optimum productivity. As the Fuzzy controller provides always the two values of Dilution rate for control action and by selecting the value nearer to the operating point, it is found to give stable and faster responses than conventional PI controller. The PI controller results in wash out condition or switch over from initial lower input dilution rate to higher input dilution rate or vice versa. Thus, Fuzzy control is found to overcome the control problems of PI controller due to the input multiplicities near optimal productivity. It is interesting to note that the present fuzzy logic controller is giving superior performance like previously proposed nonlinear controller by authors (Reddy, G.P. and Chidambaram, M (1995) ) to overcome the control problems due to input multiplicities and however fuzzy logic controller is less computationally involved than nonlinear controller.

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Keywords
Fuzzy logic control, Bioreactor, Input Multiplicities, Near optimal productivity.