Fuzzy logic control of biohydrogen production using microbial electrolysis cell (MEC) reactor for storage application / Khew Mun Hong, Gabriel

Khew , Gabriel Mun Hong (2021) Fuzzy logic control of biohydrogen production using microbial electrolysis cell (MEC) reactor for storage application / Khew Mun Hong, Gabriel. Masters thesis, Universiti Malaya.

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      The content of this work presents the implementation of Fuzzy Logic Control (FLC) on a microbial electrolysis cell (MEC) for storage applications. Hydrogen has been touted as one of the potential alternative sources of renewable energy to the depleting fossil fuels. MEC is one of the most extensively studied methods of hydrogen production. One of main advantages of MEC is its ability to utilize organic wastes as the substrates for biohydrogen production. However, the MEC system involves microbial interaction contributes to the system’s nonlinear behaviour. Due to its high complexity, a precise process control system must be implemented to ensure the MEC systems could operate in a stable manner. Proportional Integral-Derivative (PID) controller has been one of the pioneer control loop mechanism. However, the conventional PID controller has its drawbacks such as the lacking in its ability to adapt properly in the presence of disturbance within a nonlinear system. Advanced process control mechanism known as FLC can prove to be a better solution to be implemented on a nonlinear system due to its similarity in human-natured thinking. In this research, the FLC is implemented onto the MEC system and its performance is evaluated using several control schemes such as constant setpoints, multiple setpoints tracking, internal disturbance rejection, external disturbance rejection and noise disturbance rejection to ensure a timely readiness of hydrogen storage. Similar evaluations are conducted on Proportional-Integral (PI) and PID controllers as well for comparison purposes. FLC has generally resulted in desirable outcomes over the PI and PID controllers. Integral absolute error (IAE) evaluation shows improvement ranging from 42.3% to 99.4% from PI controller to FLC and 36.2% to 99.4% from PID controller to FLC can be obtained from this study.

      Item Type: Thesis (Masters)
      Additional Information: Dissertation (M.A.) - Faculty of Engineering, Universiti Malaya, 2021.
      Uncontrolled Keywords: Fuzzy Logic Control; Nonlinear; Microbial Electrolysis Cell; Fuel Cell; Renewable Energy; Simulink
      Subjects: T Technology > TA Engineering (General). Civil engineering (General)
      Divisions: Faculty of Engineering
      Depositing User: Mrs Rafidah Abu Othman
      Date Deposited: 14 Apr 2022 02:48
      Last Modified: 14 Apr 2022 02:48
      URI: http://studentsrepo.um.edu.my/id/eprint/13201

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