Abstract
Microbial fuel cell (MFC) is a kind of promising clean power supply energy equipment, but serious nonlinearities and disturbances exist when the MFC runs, and it is an important topic to guarantee that the output voltage reaches the setting value quickly and smoothly. Regulating the feeding flow is an effective way to achieve this goal, and especially, the satisfactory results can be achieved by regulating anode feeding flow. In this work, a feedforward fuzzy logic PID algorithm is proposed. The fuzzy logic system is introduced to deal with the non-linear dynamics of MFC, and corresponding PID parameters are calculated according to defuzzification. The magnitude value of the current density is used to simulate the value of the external load. The simulation results indicate that the MFC output voltage can track the setting value quickly and smoothly with the proposed feedforward fuzzy logic PID algorithm. The proposed algorithm is more efficient and robust with respect to anti-disturbance performance and tracking accuracy than other three control methods.
摘要
微生物燃料电池(MFC)是一种具有应用前景的清洁供电能源设备, 但在其运行过程中存在着严 重的非线性和干扰, 保证其输出电压快速、平稳地达到设定值是一个重要课题. 调节进料流量是实现 这一目标的有效途径, 特别是通过调节阳极进料流量可以达到满意的效果. 本文使用了一种前馈模糊 逻辑PID 算法, 引入模糊逻辑系统来处理MFC 的非线性动态特性, 并根据解模糊化原理计算出相应 的PID 参数. 电流密度的大小值用于模拟外部负载的大小. 仿真结果表明, 前馈模糊逻辑PID 方法能 够快速、平稳地跟踪设定值. 与其他三种控制方法相比, 该方法跟踪精度较佳, 抗负载突发干扰的能 力较强.
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References
KADIER A, KALIL M S, ABDESHAHIAN P, CHANDRASEKHAR K, MOHAMED A, AZMAN N F, LOGRONO W, SIMAYI Y, HAMID A A. Recent advances and emerging challenges in microbial electrolysis cells (MECs) for microbial production of hydrogen and value-added chemicals [J]. Renewable and Sustainable Energy Reviews, 2016, 61: 501–525.
JAFARY T, DAUD W R W, GHASEMI M, KIM B H, MD JAHIM J, ISMAIL M, LIM S S. Biocathode in microbial electrolysis cell; present status and future prospects [J]. Renewable and Sustainable Energy Reviews, 2015, 47: 23–33.
LOGAN B E, HAMELERS B, ROZENDAL R, SCHRÖDER U, KELLER J, FREGUIA S, AELTERMAN P, VERSTRAETE W, RABAEY K. Microbial fuel cells: Methodology and technology [J]. Environmental Science & Technology, 2006, 40(17): 5181–5192.
BOGHANI H C, KIM J R, DINSDALE R M, GUWY A J, PREMIER G C. Analysis of the dynamic performance of a microbial fuel cell using a system identification approach [J]. Journal of Power Sources, 2013, 238: 218–226.
LI Xiao-min, CHENG Ka-yu, WONG J W C. Bioelectricity production from food waste leachate using microbial fuel cells: Effect of NaCl and pH [J]. Bioresource Technology, 2013, 149: 452–458.
LOGAN B, CHENG Shao-an, WATSON V, ESTADT G. Graphite fiber brush anodes for increased power production in air-cathode microbial fuel cells [J]. Environmental Science & Technology, 2007, 41(9): 3341–3346.
DI LORENZO M, SCOTT K, CURTIS T P, HEAD I M. Effect of increasing anode surface area on the performance of a single chamber microbial fuel cell [J]. Chemical Engineering Journal, 2010, 156(1): 40–48.
REN H, TORRES C I, PARAMESWARAN P, RITTMANN B E, CHAE J. Improved current and power density with a micro-scale microbial fuel cell due to a small characteristic length [J]. Biosensors and Bioelectronics, 2014, 61: 587–592.
CHENG Shao-an, LOGAN B E. Increasing power generation for scaling up single-chamber air cathode microbial fuel cells [J]. Bioresource Technology, 2011, 102(6): 4468–4473.
BOROLE A P, HAMILTON C Y, VISHNIVETSKAYA T, LEAK D, ANDRAS C. Improving power production in acetate-fed microbial fuel cells via enrichment of exoelectrogenic organisms in flow-through systems [J]. Biochemical Engineering Journal, 2009, 48(1): 71–80.
BOGHANI H C, MICHIE I, DINSDALE R M, GUWY A J, PREMIER G C. Control of microbial fuel cell voltage using a gain scheduling control strategy [J]. Journal of Power Sources, 2016, 322: 106–115.
BOGHANI H C, DINSDALE R M, GUWY A J, PREMIER G C. Sampled-time control of a microbial fuel cell stack [J]. Journal of Power Sources, 2017, 356: 338–347.
LI Hui-min, WANG Xiao-bo, SONG Shang-bin, LI Hao. Vehicle control strategies analysis based on PID and fuzzy logic control [J]. Procedia Engineering, 2016, 137: 234–243.
YAN Min-xiu, FAN Li-ping. Constant voltage output in two-chanber microbial fuel cell under fuzzy PID control [J]. International Journal of Electrochemical Science, 2013, 8: 3321–3332.
WANG Guan-wen, FENG Chun-hua. Electrochemical polymerization of hydroquinone on graphite felt as a pseudocapacitive material for application in a microbial fuel cell [J]. Polymers, 2017, 9(12): 220.
LI Jing, LI Jie, LAI Yan-qing, SONG Hai-sheng, ZHANG Zhi-an, LIU Ye-xiang. Influence of KOH activation techniques on pore structure and electrochemical property of carbon electrode materials [J]. Journal of Central South University of Technology, 2006, 13(4): 360–366.
LAI Bin, WANG Peng, LI Hao-ran, DU Zhu-wei, WANG Lijuan, BI Si-chao. Calcined polyaniline-iron composite as a high efficient cathodic catalyst in microbial fuel cells [J]. Bioresource Technology, 2013, 131: 321–324.
OLIVEIRA V B, SIMÖES M, MELO L F, PINTO A M F R. A 1D mathematical model for a microbial fuel cell [J]. Energy, 2013, 61: 463–471.
PINTO R P, SRINIVASAN B, MANUEL M F, TARTAKOVSKY B. A two-population bio-electrochemical model of a microbial fuel cell [J]. Bioresource Technology, 2010, 101(14): 5256–5265.
BATSTONE D J, KELLER J, ANGELIDAKI I, KALYUZHNYI S V, PAVLOSTATHIS S G, ROZZI A, SANDERS W T M, SIEGRIST H, VAVILIN V A. The IWA anaerobic digestion model No 1 (ADM1) [J]. Water Science and Technology, 2002, 45(10): 65–73.
CHEN Jia-yi, ZHAO Lin, LI Nan, LIU Hang. A microbial fuel cell with the three-dimensional electrode applied an external voltage for synthesis of hydrogen peroxide from organic matter [J]. Journal of Power Sources, 2015, 287: 291–296.
ZENG Ying-zhi, CHOO Y F, KIM B H, WU Ping. Modeling and simulation of two-chamber microbial fuel cell [J]. Journal of Power Sources, 2010, 195(1): 79–89.
VOJTESEK J, DOSTÁL P. Nostradamus 2014: Prediction, modeling and analysis of complex systems [M]. Cham: Springer International Publishing, 2014: 195–204.
AN Ai-min, LIU Yun-li, ZHANG Hao-chen, ZHENG Chen-dong, FU Juan. Dynamic performance analysis and neural network predictive control of microbial fuel cell [J]. CIESC Journal, 2017, 68: 1090–1098.
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Foundation item: Project(61563032) supported by the National Natural Science Foundation of China; Project(18JR3RA133) supported by Gansu Basic Research Innovation Group, China
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Luo, Qz., An, Am., Zhang, Hc. et al. Non-linear performance analysis and voltage control of MFC based on feedforward fuzzy logic PID strategy. J. Cent. South Univ. 26, 3359–3371 (2019). https://doi.org/10.1007/s11771-019-4259-4
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DOI: https://doi.org/10.1007/s11771-019-4259-4