Optimization of electrochemical parameters in microbial fuel cell system based on Fuzzy-PID and CMAC neural network


  • Chengcai Fu School of Electrical Engineering and Automation, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353 and School of Mechanical Electronic & Information Engineering and University of Mining & Technology, Beijing 100083
  • Fengying Ma School of Electrical Engineering and Automation, Qilu University of Technology ,Shandong Academy of Sciences, Jinan 250353




Microbial fuel cells, electrochemical parameters, fuzzy optional algorithm, CMAC neural network


Due to the extensive application prospects on wastewater treatment and new energy development, microbial fuel cells (MFCs) have gained more and more attention by many scholars all over the world. The bioelectrochemical reaction in MFC system is highly complex, serious nonlinear and time-delay dynamic process, in which the optimal control of electrochemical parameters is still a considerable challenge. A new optimal control scheme for MFC system which combines proportional integral derivative (PID) controller with parameters fuzzy optional algorithm and cerebellar model articulation controller (CMAC) neural network was proposed. The simulation results demonstrate that the proposed control scheme has rapider response, better control effect and stronger anti-interference ability than Fuzzy PID controller by taking constant voltage output of MFC under the different load disturbances as example.


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How to Cite

Fu, C., & Ma, F. (2019). Optimization of electrochemical parameters in microbial fuel cell system based on Fuzzy-PID and CMAC neural network. Journal of Electrochemical Science and Engineering, 9(2), 135–142. https://doi.org/10.5599/jese.636



Bioelectrochemistry & Fuel Cells