Fuzzy Integral Sliding Mode Control Based on Microbial Fuel Cell
Author(s) -
Lei Lian,
Peng Ji,
Tianyu Ouyang,
Fengying Ma,
Shanwen Xu,
Chao Gao,
Jing Liu
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/6670039
Subject(s) - robustness (evolution) , control theory (sociology) , microbial fuel cell , sliding mode control , fuzzy logic , fuzzy control system , computer science , renewable energy , integral sliding mode , power (physics) , control engineering , control (management) , electricity generation , engineering , chemistry , artificial intelligence , biochemistry , physics , quantum mechanics , nonlinear system , electrical engineering , gene
Microbial fuel cell (MFC) is a renewable clean energy. Microorganisms are used as catalysts to convert the chemical energy of organic matter in the sewage into electrical energy to realize sewage treatment and recover energy at the same time. It has good development prospects. However, the output power of MFC is affected by many factors, and it is difficult to achieve a stable voltage output. For the control-oriented single-chamber MFC, a fuzzy integral sliding mode control is designed. The continuous adjustment of the sliding surface ensures that the system only moves on the sliding surface, which eliminates the arrival stage and improves robustness. For chattering existing in the system, the control scheme is further optimized to obtain fuzzy integral sliding mode control, and the fuzzy module adaptively adjusts the control parameters according to the system state, which effectively reduces the system chattering. Experiments prove that the control scheme reduces chattering while ensuring the stable output of the system.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom