Wang, J. B., Yang, B., Zeng, C. Y., Chen, Y. J., Yu, T., et al. (2021). Recent advances and summarization of fault diagnosis techniques for proton exchange membrane fuel cell systems: A critical overview. Journal of Power Sources, 500, 229932.
Yang, B., Wang, J. B., Yu, L., et al. (2020). A critical survey on proton exchange membrane fuel cell parameter estimation using meta-heuristic algorithms. Journal of Cleaner Production, 265, 121660.
Olujobi, O. J. (2020). The legal sustainability of energy substitution in Nigeria’s electric power sector: Renewable energy as alternative. Protection and Control of Modern Power Systems, 5(4), 358–369.
Yang, B., Wang, J. B., Zhang, X. S., Yu, T., Yao, W., Shu, H. C., et al. (2020). Comprehensive overview of meta-heuristic algorithm applications on PV cell parameter identification. Energy Conversion and Management, 208, 112595.
Yang, B., Yu, T., Zhang, X. S., Li, H. F., Shu, H. C., Sang, Y. Y., & Jiang, L. (2019). Dynamic leader based collective intelligence for maximum power point tracking of PV systems affected by partial shading condition. Energy Conversion and Management, 179, 286–303.
Liu, J., Wen, J. Y., Yao, W., & Long, Y. (2016). Solution to short-term frequency response of wind farms by using energy storage systems. IET Renewable Power Generation, 10(5), 669–678.
Yao, W., Jiang, L., Wen, J. Y., Wu, Q. H., & Cheng, S. J. (2015). Wide-area damping controller for power system interarea oscillations: A networked predictive control approach. IEEE Transactions on Control Systems Technology, 23(1), 27–36.
Abbaker, A. M. O., Wang, H. P., & Tian, Y. (2019). Voltage control of solid oxide fuel cell power plant based on intelligent proportional integral-adaptive sliding mode control with anti-windup compensator. Transactions of the Institute of Measurement and Control, 42(1), 116–130.
Kumar, D. S., Savier, J. S., & Biju, S. S. (2020). Micro-synchrophasor based special protection scheme for distribution system automation in a smart city. Protection and Control of Modern Power Systems, 5(1), 97–110.
Murty, V. V. S. N., & Kumar, A. (2020). Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems. Protection and Control of Modern Power Systems, 5(1), 1–20.
Tummala, A. S. L. V. (2020). A robust composite wide area control of a DFIG wind energy system for damping inter-area oscillations. Protection and Control of Modern Power Systems, 5(3), 260–269.
Yang, B., Jiang, L., Wang, L., Yao, W., & Wu, Q. H. (2016). Nonlinear maximum power point tracking control and model analysis of DFIG based wind turbine. International Journal of Electrical Power & Energy Systems, 74, 429–436.
Malik, V., Srivastava, S., Bhatnagar, M. K., & Vishnoi, M. (2021). Comparative study and analysis between solid oxide fuel cells (SOFC) and proton exchange membrane (PEM) fuel cell – A review. Materials Today: Proceedings, 47(10), 2270–2275.
Wu, L., Wu, X., Pan, L., Shen, J., Li, Y. G., & Zhang, J. L. (2019). Fuzzy model predictive control of solid oxide fuel cell with zone tracking. IFAC-PapersOnLine, 52(4), 210–215.
Yang, B., Zhong, L. E., Yu, T., Li, H. F., Zhang, X. S., Shu, H. C., Sang, Y. Y., & Jiang, L. (2019). Novel bio-inspired memetic salp swarm algorithm and application to MPPT for PV systems considering partial shading condition. Journal of Cleaner Production, 215, 1203–1222.
Yang, B., Zhang, X. S., Yu, T., Shu, H. C., & Fang, Z. H. (2017). Grouped grey wolf optimizer for maximum power point tracking of doubly-fed induction generator based wind turbine. Energy Conversion and Management, 133, 427–443.
Wang, Q., Yao, W., Fang, J. K., Ai, X. M., Wen, J. Y., Yang, X. B., Xie, H. L., & Huang, X. (2020). Dynamic modeling and small signal stability analysis of distributed photovoltaic grid-connected system with large scale of panel level DC optimizers. Applied Energy, 259, 114132.
Shen, Y., Yao, W., Wen, J. Y., He, H. B., & Jiang, L. (2019). Resilient wide-area damping control using GrHDP to tolerate communication failures. IEEE Transactions on Smart Grid, 10(3), 2547–2557.
Ferriday, T. B., & Middleton, P. H. (2021). Alkaline fuel cell technology-A review. International Journal of Hydrogen Energy, 46(35), 18489–18510.
Yang, B., Zhu, T. J., Zhang, X. S., Wang, J. B., Shu, H. C., Li, S. N., He, T. Y., Yang, L., & Yu, T. (2020). Design and implementation of battery/SMES hybrid energy storage systems used in electric vehicles: A nonlinear robust fractional-order control approach. Energy, 191, 116510.
Cheng, S., Zhao, G. J., Gao, M., et al. (2021). A new hybrid solar photovoltaic/phosphoric acid fuel cell and energy storage system; energy and exergy performance. International Journal of Hydrogen Energy, 46(11), 8048–8066.
Lin-Kwong-Chon, C., Grondin-Perez, B., Kadjo, J. J. A., et al. (2019). A review of adaptive neural control applied to proton exchange membrane fuel cell systems. Annual Review in Control, 47, 133–154.
Wee, J. H. (2014). Carbon dioxide emission reduction using molten carbonate fuel cell systems. Renewable and Sustainable Energy Reviews, 32, 178–191.
Stambouli, A. B., & Traversa, E. (2002). Solid oxide fuel cells (SOFCs): A review of an environmentally clean and efficient source of energy. Renewable and Sustainable Energy Reviews, 6(5), 433–455.
Vaishampayan, V., Vangari, A., Shah, J. (2014). Challenges and opportunities of affordable fuel cell for distributed generation. In International Conference on Non Conventional Energy (ICONCE). 16–17 Jan, Kaliyani, India, https://doi.org/10.1109/ICONCE.2014.6808734.
Yang, B., Wang, J. B., Zhang, M. T., Shu, H. C., et al. (2020). A state-of-the-art survey of solid oxide fuel cell parameter identification: Modelling, methodology, and perspectives. Energy Conversion and Management, 213, 112856.
Wu, X. J., Xu, L. F., Wang, J. H., Yang, D. N., Zhang, M. T., & Li, X. (2020). Discharge performance recovery of a solid oxide fuel cell based on a prognostic-based control strategy. Journal of Power Sources, 480, 229102.
Awryńczuk, M. (2020). Constrained computationally efficient nonlinear predictive control of solid oxide fuel cell: Tuning, feasibility and performance. ISA Transactions, 99, 270–289.
Das, T., Roy, R., & Mandal, K. K. (2020). Impact of the penetration of distributed generation on optimal reactive power dispatch. Protection and Control of Modern Power Systems, 5(31), 332–357.
Huang, Z., Fang, B. L., & Deng, J. (2020). Multi-objective optimization strategy for distribution network considering V2G enabled electric vehicles in building integrated energy system. Protection and Control of Modern Power Systems, 5(1), 48–55.
Li, Z. R., Xu, J., Wang, K. Y., Wu, P., & Li, G. J. (2020). FPGA-based real-time simulation for EV station with multiple high-frequency chargers based on C-EMTP algorithm. Protection and Control of Modern Power Systems, 5(4), 283–293.
Pohjoranta, A., Halinen, M., Pennanen, J., & Kiviaho, J. (2015). Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data. Journal of Power Sources, 277, 239–250.
Deng, Z.H.; Li, X. (2007). The design for model and control of solid oxide fuel cell electrical characteristic. In Chinese Control Conference (CHICC). 26–31 July, Zhangjiajie, China, https://doi.org/10.1109/CHICC.2006.4347521.
Bao, C., Wang, Y., Feng, D. L., Jiang, Z. Y., & Zhang, X. X. (2018). Macroscopic modeling of solid oxide fuel cell (SOFC) and model-based control of SOFC and gas turbine hybrid system. Progress in Energy and Combustion Science, 66, 83–140.
Wang, K., Hissel, D., Pera, M. C., et al. (2011). A review on solid oxide fuel cell models. International Journal of Hydrogen Energy, 36(12), 7212–7228.
Li, Y. H., Choi, S. S., & Rajakaruna, S. (2005). An analysis of the control and operation of a solid oxide fuel-cell power plant in an isolated system. IEEE Transactions on Energy Conversion, 20(2), 381–387.
Chaisantikulwat, A., Meadows, E. S., & Diaz-Goano, C. (2008). Dynamic modelling and control of planar anode-supported solid oxide fuel cell. Computers & Chemical Engineering, 32(10), 2365–2381.
Huo, H. B., Zhu, X. J., Hu, W. Q., Tu, H. Y., Li, J., & Yang, J. (2008). Nonlinear model predictive control of SOFC based on a Hammerstein model. Journal of Power Sources, 185(1), 338–344.
Aguiar, P., Adjiman, C. S., & Brandon, N. P. (2005). Anode-supported intermediate-temperature direct internal reforming solid oxide fuel cell: II. Model-based dynamic performance and control. Journal of Power Sources, 147(1–2), 136–147.
Sendjaja, A. Y., & Kariwala, V. (2011). Decentralized control of solid oxide fuel cells. IEEE Transactions on Industrial Informatics, 7(2), 163–170.
Spivey, B.J., Hedengren, J.D., Edgar, T.F. (2012). Constrained control and optimization of tubular solid oxide fuel cells for extending cell lifetime. In American Control Conference (ACC), 27–29 June, Montreal, QC, Canada, https://doi.org/10.1109/ACC.2012.6315334.
Leung, M., Park, G., Radisavljevic-Gajic, V. (2013). Control of solid oxide fuel cells: An overview. In Asian Control Conference (ASCC). 23–26, Istanbul, Turkey. https://doi.org/10.1109/ASCC.2013.6606314.
Chen, J., Yao, W., Zhang, C. K., Ren, Y., & Jiang, L. (2019). Design of robust MPPT controller for grid-connected PMSG-Based wind turbine via perturbation observation based nonlinear adaptive control. Renewable Energy, 134, 478–495.
Peng, J. X., Huang, J., Wu, X. L., Xu, Y. W., Chen, H. C., & Li, X. (2021). Solid oxide fuel cell (SOFC) performance evaluation, fault diagnosis and health control: A review. Journal of Power Sources, 505, 230058.
Schafer, F., Egger, S., Steiner, D., Carre, M., & Eichel, R. A. (2022). Control of oxygen-to-carbon ratio and fuel utilization with regard to solid oxide fuel cell systems with anode exhaust gas recirculation: A review. Journal of Power Sources, 524, 231077.
Yang, B., Zhang, M. T., Zhang, X. S., Wang, J. B., Shu, H. C., Li, S. N., He, T. Y., Yang, L., & Yu, T. (2020). Fast atom search optimization based MPPT design of centralized thermoelectric generation system under heterogeneous temperature difference. Journal of Cleaner Production, 248, 119301.
Yang, B., Li, J. L., Li, Y. L., et al. (2022). A critical survey of proton exchange membrane fuel cell system control: Summaries, advances, and perspectives. International Journal of Hydrogen Energy, 47, 9986–10020.
Dijoux, E., Steiner, N. Y., Benne, M., et al. (2017). A review of fault tolerant control strategies applied to proton exchange membrane fuel cell systems. Journal of Power Sources, 359, 119–133.
Singh, M., Zappa, D., & Comini, E. (2021). Solid oxide fuel cell: Decade of progress, future perspectives and challenges. International Journal of Hydrogen Energy, 46(54), 27643–27674.
Liu, S. M., Deng, Z. F., Xu, G. Z., Li, B. R., Song, P. X., & Wang, S. R. (2020). Industrialization status of solid oxide fuel cell (SOFC) in Europe. Journal of Beijing University of science and technology, 42(3), 278–288.
Komatsu, Y., Kimijima, S., & Szmyd, J. S. (2013). Numerical analysis on dynamic behavior of solid oxide fuel cell with power output control scheme. Journal of Power Sources, 223, 232–245.
Bhattacharyya, D., & Rengaswamy, R. (2009). A review of solid oxide fuel cell (SOFC) dynamic models. Industrial & Engineering Chemistry Research, 48(13), 6068–6086.
Li, Y. G., Shen, J., & Lu, J. H. (2011). Constrained model predictive control of a solid oxide fuel cell based on genetic optimization. Journal of Power Sources, 196(14), 5873–5880.
Mazumder, S. K., Acharya, K., Haynes, C. L., et al. (2004). Solid-oxide-fuel-cell performance and durability: Resolution of the effects of power-conditioning systems and application loads. IEEE Transactions on Power Electronics, 19(5), 1263–1278.
Murshed, A. K. M. M., Huang, B., & Nandakumar, K. (2007). Control relevant modeling of planer solid oxide fuel cell system. Journal of Power Sources, 163(2), 830–845.
Yang, J., Qin, S., Zhang, W. Y., Ding, T. F., Zhou, B., Li, X., & Jian, L. (2017). Improving the load-following capability of a solid oxide fuel cell system through the use of time delay control. International Journal of Hydrogen Energy, 42(2), 1221–1236.
Wu, X. J., & Gao, D. H. (2018). Optimal robust control strategy of a solid oxide fuel cell system. Journal of Power Sources, 374, 163–181.
Zhang, L., Li, X., Jiang, J. H., Li, S. H., Yang, J., & Li, J. (2015). Dynamic modeling and analysis of a 5-kW solid oxide fuel cell system from the perspectives of cooperative control of thermal safety and high efficiency. International Journal of Hydrogen Energy, 40(1), 456–476.
Xi, H.D., Varigonda, S., Jing, B.Y. (2010). Dynamic modeling of a solid oxide fuel cell system for control design. In Proceeding of the 2010 American Control Conference (ACC). 30 June-2 July, Baltimore, MD, USA, https://doi.org/10.1109/ACC.2010.5531009.
Liu, J. K. (2011). Matlab simulation of advanced PID control. Electronic Industry Press.
Sorrentino, M., Pianese, C., & Guezennec, Y. G. (2008). A hierarchical modeling approach to the simulation and control of planar solid oxide fuel cells. Journal of Power Sources, 180(1), 380–392.
Hajimolana, S. A., & Soroush, M. (2009). Dynamics and control of a tubular solid-oxide fuel cell. Industrial & Engineering Chemistry Research, 48(13), 6112–6125.
Cheng, Y., Liu, D. Y., Zhang, L. T., Feng, X. D. (2008). Modeling and simulation analysis of solid oxide fuel cell system for marine equipment. In Chinese Automation Congress (CAC), Xi’an, China, https://doi.org/10.1109/CAC.2018.8623226.
Vrecko, D., Nerat, M., et al. (2018). Feedforward-feedback control of a solid oxide fuel cell power system. International Journal of Hydrogen Energy, 43(12), 6352–6363.
Kupecki, J., Motylinski, K., Zurawska, A., Kosiorek, M., & Ajdys, L. (2019). Numerical analysis of an SOFC stack under loss of oxidant related fault conditions using a dynamic non-adiabatic model. International Journal of Hydrogen Energy, 44(38), 21148–21161.
Singh, S., Tayal, V. K.,Singh, H. P., Yadav, V. K. (2021). Performance Enhancement of solid oxide fuel cell by employing PI controller and PID controller with filter derivative. In: 2021 IEEE International Power and Renewable Energy Conference(IPRECON). 24–26 Sept., Kollam, India, https://doi.org/10.1109/IPRECON52453.2021.9640720.
Zhang, L., Xie, H.T., Wang, F., Xie, C., Liu, R.H., Tang, W.H., Zhou, W.B., Wang, G. Q. (2021). A multi-loop control strategy for 5 kW solid oxide fuel cell hybrid system. In 2021 China Automation Congress (CAC). 22–24 Oct, Beijing, China, 1109/CAC53003.2021.9727452.
Marzooghi, H., & Raoofat, M. (2012). Improving the performance of proton exchange membrane and solid oxide fuel cells under voltage flicker using Fuzzy-PI controller. International Journal of Hydrogen Energy, 37(9), 7796–7806.
Xu, D. Z.; Yan, W. X.; Ji, N. (2016). RBF neural network based adaptive constrained PID control of a solid oxide fuel cell. In Chinese Control and Decision Conference (CCDC). 28–30 May, Yinchuan, China, https://doi.org/10.1109/CCDC.2016.7531681.
Cao, H. L., & Li, X. (2016). Thermal management-oriented multivariable robust control of a kW-scale solid oxide fuel cell stand-alone system. Transactions on Energy Conversion, 31(2), 1–10.
Cheng, H., Jing, S. W., Xu, Y. W., Deng, Z. H., Li, J., & Li, X. (2016). Control-oriented modeling analysis and optimization of planar solid oxide fuel cell system. International Journal of Hydrogen Energy, 41(47), 22285–22304.
Zhang, T., Li, H.L., Tu, X. W., Pang, H. Z.,Huang, Y. (2021). Optimization of SOC fractional PID control parameters for solid oxide battery based on improved firefly algorithm. In: 2021 3rd International Conference on Industrial Artificial Intelligence(IAI). 8–11 Nov, Shenyang, China, DOI: https://doi.org/10.1109/IAI53119.2021.9619450.
Nayeripour, M., & Hoseintabar, M. (2013). A new control strategy of solid oxide fuel cell based on coordination between hydrogen fuel flow rate and utilization factor. Renewable and Sustainable Energy Reviews, 27(27), 505–514.
Xu, D. Z., Jiang, B., & Liu, F. (2016). Improved data driven model free adaptive constrained control for a solid oxide fuel cell. IET Control Theory & Applications, 10(12), 1412–1419.
Sun, L. M., & Yang, B. (2020). Nonlinear robust fractional-order control of battery/SMES hybrid energy storage systems. Power System Protection and Control, 48(22), 76–83.
Yang, B., Yu, T., Shu, H. C., Zhang, Y. M., Chen, J., Sang, Y. Y., & Jiang, L. (2018). Passivity-based sliding-mode control design for optimal power extraction of a PMSG based variable speed wind turbine. Renewable Energy, 119, 577–589.
Yang, B., Yu, T., Shu, H. C., Dong, J., & Jiang, L. (2018). Robust sliding-mode control of wind energy conversion systems for optimal power extraction via nonlinear perturbation observers. Applied Energy, 210, 711–723.
Sun, J., & Kolmanovsky, I. (2005). Load governor for fuel cell oxygen starvation protection: A robust nonlinear reference governor approach. Transactions on Control Systems Technology, 13(6), 911–920.
Fardadi, M., Mueller, F., & Jabbari, F. (2010). Feedback control of solid oxide fuel cell spatial temperature variation. Journal of Power Sources, 195(13), 4222–4233.
Huo, H. B., Yang, H. D., Xu, K., Kuang, X. H., & Xu, J. X. (2021). Survey an H∞ robust control of the solid oxide fuel cell. Mathematical Problems in Engineering, 2021, 6693971.
Allag, T., & Das, T. (2012). Robust control of solid oxide fuel cell ultracapacitor hybrid system. Transactions on Control Systems Technology, 20(1), 1–10.
Dötschel, T., Rauh, A., Senkel, L., Aschemann, H. (2013). Experimental validation of interval-based sliding mode control for solid oxide fuel cell systems. In European Control Conference (ECC), 17–19 July, Zurich, Switzerland, https://doi.org/10.23919/ECC.2013.6669534.
Rauh, A., Senkel, L., & Aschemann, H. (2015). Interval-based sliding mode control design for solid oxide fuel cells with state and actuator constraints. Transactions on Industrial Electronics, 62(8), 5208–5217.
Am, O. A., Wang, H. P., & Tian, Y. (2022). Enhanced model-free discrete-time adaptive terminal sliding-mode control for SOFC power plant with input constraints. Arabian Journal for Science and Engineering, 47, 2851–2864.
Jurado, F. (2006). Predictive control of solid oxide fuel cells using fuzzy Hammerstein models. Journal of Power Sources, 158(1), 245–253.
Wang, X. R., Huang, B., & Chen, T. W. (2007). Data-driven predictive control for solid oxide fuel cells. Journal of Process Control, 17(2), 103–114.
Sanandaji, B. M., Vincent, T. L., Colclasure, A. M., & Kee, R. J. (2011). Modeling and control of tubular solid-oxide fuel cell systems: II. Nonlinear model reduction and model predictive control. Journal of Power Sources, 196(1), 208–217.
Kupilik, M. J., & Vincent, T. L. (2013). Control of a solid oxide fuel cell system with sensitivity to carbon formation. Journal of Power Sources, 222, 267–276.
Horalek, R., Hlava, J. (2015). Multilinear model predictive control of solid oxide fuel cell output voltage. In Electronics, Control, Measurement, Signals & Their Application to Mechatronics (ECMSM), 22–24 June, Liberec, Czech Republic, https://doi.org/10.1109/ECMSM.2015.7208702.
Horalek, R., Hlava, J. (2015). Multiple model predictive control of grid connected solid oxide fuel cell for extending cell life time. In Mediterranean Conference on Control and Automation (MED). 16–19 June, Torremolinos, Spain, https://doi.org/10.1109/MED.2015.7158768.
Miaomiao, H., Zhou, B.Z. (2017). The multi-parameter programming control of solid oxide fuel cell. In International Conference on Information Science and Control Engineering (ICISCE), 21-23 July, Changsha, China, pp. 1278-1281.
Frenkel, W., Kersten, J., Aschemann, H.,Rauh, A. (2021). Model predictive control as an industrially applicable approach for power control of solid oxide fuel cells. In 2021 25th International Conference on Methods and Models in Automation and Robotics (MMAR). 23–26 Aug, Miedzyzdroje, Poland, https://doi.org/10.1109/MMAR49549.2021.9528484.
Zhang, X. W., Chan, S. H., Ho, U. K., Li, J., Li, G. J., & Feng, Z. P. (2008). Nonlinear model predictive control based on the moving horizon state estimation for the solid oxide fuel cell. International Journal of Hydrogen Energy, 33(9), 2355–2366.
Yang, J., Li, X., Mou, H. G., & Jian, L. (2009). Predictive control of solid oxide fuel cell based on an improved Takagi-Sugeno fuzzy model. Journal of Power Sources, 193(2), 699–705.
Murshed, A. K. M. M., Huang, B., & Nandakumar, K. (2010). Estimation and control of solid oxide fuel cell system. Computers & Chemical Engineering, 34(1), 96–111.
Bhattacharyya, D., & Rengaswamy, R. (2010). System identification and nonlinear model predictive control of a solid oxide fuel cell. Industrial & Engineering Chemistry Research, 49(10), 4800–4808.
Lee, S. M., Kwon, O. M., & Park, J. H. (2012). Predictive control for sector bounded nonlinear model and its application to solid oxide fuel cell systems. Applied Mathematics & Computation, 218(18), 9296–9304.
Deng, Z. H., Gao, H. L., Li, X., Jiang, J. H., Yang, J., & Qin, Y. (2010). Generalized predictive control for fractional order dynamic model of solid oxide fuel cell output power. Journal of Power Sources, 195(24), 8097–8103.
Jiang, J. H., Li, X., Deng, Z. H., Yang, J., Zhang, Y. H., & Li, J. (2012). Thermal management of an independent steam reformer for a solid oxide fuel cell with constrained generalized predictive control. International Journal of Hydrogen Energy, 37(17), 12317–12331.
Jiang, J. H.; Li, X.; Li, J. (2016). The high efficiency cooperative control of power and temperature of a stand-alone solid oxide fuel cell system with an air bypass valve. In Chinese Automation Congress (CAC), 27–29 Nov, WuHan, China, https://doi.org/10.1109/CAC.2015.7382680.
Jiang, J. H., Shen, T., Deng, Z. H., Fu, X. W., Li, J., & Li, X. (2018). High efficiency thermoelectric cooperative control of a stand-alone solid oxide fuel cell system with an air bypass valve. Energy, 152, 13–26.
Boubaker, B., Houari, K., Ahmed, B. (2021). Solid oxide fuel cell power management based on a predictive controller. In: 2020 6th International Symposium on New and Renewable Energy (SIENR), 13–14 Oct, Ghadaia, Algeria, https://doi.org/10.1109/SIENR50924.2021.9631888.
Spivey, B. J., & Edgar, T. F. (2012). Dynamic modeling, simulation, and MIMO predictive control of a tubular solid oxide fuel cell. Journal of Process Control, 22(8), 1502–1520.
Liu, Y. L., Chau, T. K., Zhang, X. N., Hu, Y. J. (2021). A novel adaptive model predictive control strategy of solid oxide fuel cell in power systems. In: 2021 31st Australasian Universities Power Engineering Conference (AUPEC), 26–30 Sept., Perth, Australia. https://doi.org/10.1109/AUPEC52110.2021.9597737.
Zhang, G. L. (2002). Fuzzy control and its application in MATLAB. [M]. Xi’an Jiaotong University.
Corcau, J. I., Dinca, L., Grigorie, T. L. (2011). Fuzzy logic controller development for a solid oxide fuel cell system. In International Symposium on Computational Intelligence & Informatics (CINTI), 21–22 Nov, Budapest, Hungary, https://doi.org/10.1109/CINTI.2011.6108487.
Bhuyan, K.C.; Mahapatra, K. An intelligent control of solid oxide fuel cell voltage. In: International Conference on Power and Energy Systems (ICPES), 22–24 Dec., 2011, Chennai, India, pp. 1–6, DOI: https://doi.org/10.1109/ICPES.2011.6156613.
Li, S. H., Gong, L., Yang, Y. P. (2017). Fault tolerant control of an anode offgas recycle based SOFC system. In American Control Conference (ACC), 24–26 May, Seattle, WA, USA, https://doi.org/10.23919/ACC.2017.7963587.
Sun, Y. L., Ghantasala, S., El-Farra, N. H. (2010). Monitoring and fault-tolerant control of distributed power generation: Application to solid oxide fuel cells. In American Control Conference ACC, 30 June-2 July, Baltimore, MD, USA, https://doi.org/10.1109/ACC.2010.5531012.
Sun, Y. L.; El-Farra, N. H. (2011). Robust fault detection and reconfigurable control of distributed energy generation systems. In American Control Conference (ACC), 29 June-1 July, San Francisco, CA, USA, https://doi.org/10.1109/ACC.2011.5991316.
Wu, X. J., & Gao, D. H. (2017). Optimal fault-tolerant control strategy of a solid oxide fuel cell system. Journal of Power Sources, 364, 163–181.
Wu, X. J., & Gao, D. H. (2017). Fault tolerance control of SOFC systems based on nonlinear model predictive control. International Journal of Hydrogen Energy, 42(4), 2288–2308.
Xue, T., Wu, X. L., Zhao, D. Q., et al. (2019). Fault-tolerant control for steam fluctuation in SOFC system with reforming units. International journal of hydrogen energy, 44(41), 23360–23376.
Ji, N., Xu, D. Z., & Liu, F. (2016). A novel adaptive neural network constrained control for solid oxide fuel cells via dynamic anti-windup. Neurocomputing, 214, 134–142.
Xi, L., Yu, T., Yang, B., Zhang, X. S., & Qiu, X. Y. (2016). A wolf pack hunting strategy based virtual tribes control for automatic generation control of smart grid. Applied Energy, 178, 198–211.
Hajimolana, S. A., Hussain, M. A., Daud, W., et al. (2012). Neural network predictive control of a SOFC fuelled with ammonia. International Journal of Electrochemical Science, 7(4), 3737–3749.
Hajimolana, S. A., Tonekabonimoghadam, S. M., Hussain, M. A., Chakrabarti, M. H., Jayakumar, N. S., & Hashim, M. A. (2013). Thermal stress management of a solid oxide fuel cell using neural network predictive control. Energy, 62(30), 320–329.
Li, J. W., Yu, T., & Yang, B. (2021). A data-driven output voltage control of solid oxide fuel cell using multi-agent deep reinforcement learning. Applied Energy, 304(505), 117541.
Li, J. W., & Yu, T. (2021). Optimal adaptive control for solid oxide fuel cell with operating constraints via large-scale deep reinforcement learning. Control Engineering Practice, 2021(117), 104951.
Li, J. W., & Yu, T. (2021). A novel data-driven controller for solid oxide fuel cell via deep reinforcement learning. Applied Energy, 2021(321), 128929.
Wu, X. J., Yang, D. N., Wang, J. H., & Li, X. (2019). Temperature gradient control of a solid oxide fuel cell stack. Journal of Power Sources, 414, 345–353.
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