Model predictive control of microbial fuel cell based on Kalman state estimation

Abstract Aiming at the constraints and undetectable interference in the microbial fuel cell system, a microbial fuel cell model predictive control method based on state estimation is proposed. According to the principles and actual requirements of the microbial fuel cell system, a state space model...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 1848; no. 1; p. 12063
Main Authors Wang, Mimmin, An, Aimin, Zhao, Yingying
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.04.2021
Subjects
Biochemical fuel cells
Constraint modelling
Control methods
Controllers
Fuel cells
Interference
Kalman filters
Microorganisms
Optimization
Performance prediction
Physics
Predictive control
Robust control
State estimation
State space models
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Summary:Abstract Aiming at the constraints and undetectable interference in the microbial fuel cell system, a microbial fuel cell model predictive control method based on state estimation is proposed. According to the principles and actual requirements of the microbial fuel cell system, a state space model with input constraints is established. By introducing the model predictive controller, the performance of constrained optimization control is improved. Combined with the Kalman filter estimator, the impact of unmeasured interference on the predictive controller is compensated, and the control accuracy and robustness of the system are improved. The simulation experiment finally indicate that model predictive control based on kalman state estimation makes the output voltage of system reach the desired value, the input flow meets the actual demand and the cost is optimal. In addition, it has a good ability to deal with interference.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1848/1/012063