Closed-Loop Microbial Fuel Cell Control System Designed for Online Monitoring of TOC Dynamic Characteristics in Public Swimming Pool
Abstract
:1. Introduction
- (1)
- Poor stability. As is known, the open-loop prediction of water pollutants based on output voltages of MFC-biosensors is very sensitive to internal variations and external disturbances, frequently causing the large prediction errors of water pollutants concentration [15].
- (2)
- Transient process of pollutant variation cannot be tracked and captured. According to cybernetics, the open-loop prediction must acquire the steady-state value of water pollutants concentration. However, it often takes quite long time for water pollutants concentration to be stabilized, and concentrations exceeding permissible standards may occur in the transient process of pollutants concentrations variation, which cannot be monitored at all [16].
2. Materials and Methods
2.1. Prototype of MFC-Biosensor for Online Monitoring TOC Concentration
2.2. Construction of Closed-Loop MFC-Biosensor for Online Monitoring TOC Concentration in PSP Water through Digital Simulation
2.2.1. Data Acquisition
2.2.2. Model Identification and Construction of Closed-Loop MFC-Biosensor Control System
2.3. Rapid Prototyping of the Closed-Loop MFC-Biosensor Control System for Monitoring TOC Concentration in PSP Water by Real-Time Simulation
3. Results and Discussion
3.1. Model Identification between TOC Concentration and MFC-Biosensor Output Voltage
3.1.1. Data Preprocessing
3.1.2. Model Identification and Validation from Time-Series IO Data
- (1)
- Model identification
- (2)
- Model validation
3.2. Design and Optimization of the Closed-Loop MFC-Biosensor Control System
3.3. Real-Time Simulation of the Closed-Loop MFC-Biosensor Control System for Online Monitoring TOC Concentration in PSP Water
- (1)
- Delay time (td) is the time needed for the response to reach half the final value, i.e., state-steady value (Sv), which is the prediction of closed-loop MFC-biosensor control system behaves as time approaches infinity.
- (2)
- Rise time (tr) is the time required for the response to rise from 5% to 95% of Sv.
- (3)
- Peak time (tp) is the time required for the response to reach the first peak of the overshoot.
- (4)
- Maximum overshoot (Mp) is the maximum peak value of the response curve, the amount of the Mp directly indicates the relative stability of the dynamic system.
- (5)
- Settling time (ts) is the time required for the response curve to reach and stay within 2% of the final value, i.e., state-steady value.
- (6)
- Best fit (BF) between actual TOC concentration and Sv.
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Chen, H.; Meng, X.; Liu, D.; Wang, W.; Xing, X.; Zhang, Z.; Dong, C. Closed-Loop Microbial Fuel Cell Control System Designed for Online Monitoring of TOC Dynamic Characteristics in Public Swimming Pool. Int. J. Environ. Res. Public Health 2022, 19, 13024. https://doi.org/10.3390/ijerph192013024
Chen H, Meng X, Liu D, Wang W, Xing X, Zhang Z, Dong C. Closed-Loop Microbial Fuel Cell Control System Designed for Online Monitoring of TOC Dynamic Characteristics in Public Swimming Pool. International Journal of Environmental Research and Public Health. 2022; 19(20):13024. https://doi.org/10.3390/ijerph192013024
Chicago/Turabian StyleChen, Haishan, Xiaoping Meng, Dianlei Liu, Wei Wang, Xiaodong Xing, Zhiyong Zhang, and Chen Dong. 2022. "Closed-Loop Microbial Fuel Cell Control System Designed for Online Monitoring of TOC Dynamic Characteristics in Public Swimming Pool" International Journal of Environmental Research and Public Health 19, no. 20: 13024. https://doi.org/10.3390/ijerph192013024