4.6 Article

Fuzzy Sliding Mode Control for Microbial Fuel Cells

期刊

MACHINES
卷 10, 期 5, 页码 -

出版社

MDPI
DOI: 10.3390/machines10050320

关键词

microbial fuel cell; sliding mode control; fuzzy control

资金

  1. Natural Science Foundation of Shandong Province [ZR2020QF051]
  2. National Natural Science Foundation of China [51874300, 61903207]
  3. National Natural Science Foundation of China and Shanxi Provincial People's Government Jointly Funded Project of China for Coal Base and Low Carbon [U1510115]
  4. Key Research and Development Program of Shandong Province [2019JZZY010731]

向作者/读者索取更多资源

In this study, a sliding mode controller and a fuzzy sliding mode control method were designed to address the issue of high susceptibility to external disturbances in microbial fuel cells. Simulation results demonstrated that the designed methods exhibited smaller steady-state error and overshoot compared to other control approaches.
The microbial fuel cells (MFCs) are a kind of green energy with good prospects, which provides an effective solution to the problem of unsustainable development of energy today. Aiming at the problem that MFCs are susceptible to various external disturbances, a sliding mode (SM) controller for MFCs is designed in this paper. The controller can effectively reduce the influence of external disturbance on voltage output and improve the practicability of microbial fuel cells (MFC). At the same time, aiming at the chattering problem of the basic SM control, a fuzzy sliding mode (FSM) control method is proposed by combining the fuzzy logic theory and the SM control. The design method of FSM controller is given by using Lyapunov theory. The method can adaptively adjust the parameters according to the difference between the actual value of the substrate concentration and the set value. The controller can reduce the system input chattering and the influence of external disturbances on the system output. Simulation results show that compared with SM control and backstepping control, the designed method has smaller steady-state error and overshoot.

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