A comparative study between Neural Networks (NN)-based and adaptive-PID controllers for the optimal bio-hydrogen gas production in microbial electrolysis cell reactor

Azwar, M.Y. and Hussain, M.A. and Abdul Wahab, A.K. and Zanil, M.F. (2015) A comparative study between Neural Networks (NN)-based and adaptive-PID controllers for the optimal bio-hydrogen gas production in microbial electrolysis cell reactor. In: 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering, 31 May – 4 June 2015, Copenhagen, Denmark.

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Abstract

The main challenge of the hydrogen production study for the MEC reactor is to obtain a good automatic control system due to the nonlinearity and complexity of the microbial interactions. To address this issue an integrated approach involving process modeling, optimization and advanced control has to be implemented. This work focus on the controller’s performance in the control system; neural network (NN)-based and Adaptive-PID controllers. The study has been carried out under optimal condition for the production of bio-hydrogen gas wherein the controller output are based on the correlation of the optimal current and voltage to the MEC. A Ziegler–Nichols tuning method and an adaptive gain technique have been used to design the PID controller, while the neural network controller has been designed from the inverse response of the MEC neural network model.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Bio-hydrogen gas, microbial electrolysis cell, neural network-based controller, adaptive-PID controller
Subjects: T Technology > TP Chemical technology
Divisions: Faculty of Engineering
Depositing User: Mr. Mohd Samsul Ismail
Date Deposited: 21 Sep 2015 00:31
Last Modified: 21 Sep 2015 00:31
URI: http://eprints.um.edu.my/id/eprint/14129

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