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Fuzzy logic controller implementation on a microbial electrolysis cell for biohydrogen production and storage

Fuzzy logic controller implementation on a microbial electrolysis cell for biohydrogen production and storage

作     者:Gabriel Khew Mun Hong Mohd Azlan Hussain Ahmad Khairi Abdul Wahab Gabriel Khew Mun Hong;Mohd Azlan Hussain;Ahmad Khairi Abdul Wahab

作者机构:Department of Chemical EngineeringFaculty of EngineeringUniversiti Malaya50603 Kuala LumpurMalaysia Department of Biomedical EngineeringFaculty of EngineeringUniversiti Malaya50603 Kuala LumpurMalaysia Centre for Separation Science and Technology(CSST)Faculty of EngineeringUniversiti Malaya50603 Kuala LumpurMalaysia 

出 版 物:《Chinese Journal of Chemical Engineering》 (中国化学工程学报(英文版))

年 卷 期:2021年第34卷第12期

页      面:149-159页

核心收录:

学科分类:081702[工学-化学工艺] 080703[工学-动力机械及工程] 08[工学] 0817[工学-化学工程与技术] 0807[工学-动力工程及工程热物理] 

基  金:supported by the UMRG RP006H-13ICT Project  University of Malaya  Malaysia 

主  题:Fuzzy logic control Process control Nonlinear Microbial electrolysis cell Renewable energy Hydrogen 

摘      要:This work presents the implementation of fuzzy logic control(FLC) on a microbial electrolysis cell(MEC).Hydrogen has been touted as a potential alternative source of energy to the depleting fossil fuels. MEC is one of the most extensively studied method of hydrogen production. The utilization of biowaste as its substrate by MEC promotes the waste to energy initiative. The hydrogen production within the MEC system, which involves microbial interaction contributes to the system s nonlinearity. Taking into account of the high complexity of MEC system, a precise process control system is required to ensure a wellcontrolled biohydrogen production flow rate and storage application inside a tank. Proportionalderivative-integral(PID) controller has been one of the pioneer control loop mechanism. However, it lacks the capability to adapt properly in the presence of disturbance. An advanced process control mechanism such as the FLC has proven to be a better solution to be implemented on a nonlinear system due to its similarity in human-natured thinking. The performance of the FLC has been evaluated based on its implementation on the MEC system through various control schemes progressively. Similar evaluations include the performance of Proportional-Integral(PI) and PID controller for comparison purposes. The tracking capability of FLC is also accessed against another advanced controller that is the model predictive controller(MPC). One of the key findings in this work is that the FLC resulted in a desirable hydrogen output via MEC over the PI and PID controller in terms of shorter settling time and lesser overshoot.

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