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MFC research paper focusing on neural network

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What they did

System
MFC

What worked

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Abstract

Microbial fuel cell (MFC) has serious nonlinearity and external disturbances when operating. In order to keep the ideal output of MFC under different load disturbances, an intelligent optimization control method based on BP neural network PID(BP-NN PID) is proposed. This method uses self-learning ability to tune the parameter of the PID controller. In addition, the online real-time control of the BP-NN algorithm shows the ability of the BP-NN to handle nonlinear systems. The simulation experiment finally shows that compared with traditional PID and single neuron PID, the BP-NN PID algorithm has good dynamic response, steady-state accuracy, adaptive ability, and strong robustness, which can make the output voltage of MFC meet the requirements.

Keywords

PID controllerControl theory (sociology)Nonlinear systemRobustness (evolution)Artificial neural networkVoltage

Identifiers

DOI
10.1109/CAC51589.2020.9327150
Journal
2020 Chinese Automation Congress (CAC)
Year
2020