Khan, M. J., Mathew, L., & Yadav, A. K. (2020). Novel applications of soft computing techniques for comparative analysis of maximum power point tracking in solar photo-voltaic system under perturb conditions. In Advances in Intelligent Systems and Computing (pp. 363–385). Springer Singapore. https://doi.org/10.1007/978-981-15-1532-3_16

Khan, M. J., & Choudhary, A. (2021). Maximum power point tracking techniques for PV framework under partial shaded conditions. In Artificial Intelligence, Machine Learning, and Data Science Technologies (pp. 193–204). CRC Press. https://doi.org/10.1201/9781003153405-10

Mustafa, R., Sarowa, S., Jaglan, R. R., Khan, M. J., & Agrawal, S. (2016). LTE-advanced random access mechanism for M2M communication: A review. AIP Conference Proceedings, 1715, 020036. https://doi.org/10.1063/1.4942718

Khan, M. J., Shukla, P., Mustafa, R., Chatterji, S., & Mathew, L. (2016). Different types of maximum power point tracking techniques for renewable energy systems: A survey. AIP Conference Proceedings, 1715, 020015. https://doi.org/10.1063/1.4942697

Khan, M. J., Yadav, A. K., Chatterji, S., & Mathew, L. (2015). Techno economic analysis of PV-Wind-Grid connected systems for power generation in India. 2015 Annual IEEE India Conference (INDICON), 1–5. https://doi.org/10.1109/indicon.2015.7443247

Khan, M. J., & Mathew, L. (2017). Artificial intelligence based maximum power point tracking algorithm for photo-voltaic system under variable environmental conditions. 2017 Recent Developments in Control, Automation & Power Engineering (RDCAPE), 114–119. https://doi.org/10.1109/rdcape.2017.8358251

[29] Bhandakkar, A. A., Mathew, L., Khan, M. J., Aziz, M. J. A., & Malik, H. (2023). Real-Time simulation of SVC on multi-machine 9-bus system. 2023 IEEE Conference on Energy Conversion (CENCON), 170–175. https://doi.org/10.1109/cencon58932.2023. 10368714

[28] Nezami, Md. M., Hashem, H., Equbal, Md. D., Khan, M. J., Ansari, Md. F., & Mustafa, E. E. (2024). An intelligent system for furfural estimation in the power transformers. In Lecture Notes in Electrical Engineering (pp. 339–345). Springer Nature Singapore. https://doi.org/10.1007/978-981-99-6749-0_20

[27] Khan, M. J., Akhtar, M. N., Hassan, M., Afthanorhan, A., Malik, H., Ayob, S. Md., Idris, N. R. N., & Jusoh, A. (2024). AI-Based framework for solar photovoltaic power management optimization under dynamic condition of irradiation. In Advances in Intelligent Systems and Computing (pp. 227–240). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-6352-8_15

[26] Rizwee, M., Minz, S. S., Md. Orooj, Hassnain, Md. Z., & Khan, M. J. (2019). Electric Discharge Machining Method for various Metal Matrix Composite Materials. International Journal of Innovative Technology and Exploring Engineering, 8(9), 1796–1800. https://doi.org/10.35940/ijitee.i8112.078919

[25] Khan, M. (2019). Artificial intelligence based maximum power point tracking controller for fuel cell system. European Journal of Electrical Engineering, 21(3), 297–302. https://doi.org/10.18280/ejee.210306

[24] Zishan Ahmad, Mohammad Junaid Khan, & Md Naqui Akhtar. (2022). A critical review of hybrid electric vehicles. Journal of Advanced Research in Applied Sciences and Engineering Technology, 29(1), 283–294. https://doi.org/10.37934/araset.29.1.283294

[23] Khan, M. J., Mustafa, R., & Pal, P. (2023). Comparative analysis of various global maximum power point tracking techniques for fuel cell frameworks. Journal of Autonomous Intelligence, 6(2), 703. https://doi.org/10.32629/jai.v6i2.703

[22] Hannan, S. A., Pushparaj, P., Khan, M. J., Kumar, A., & Kaur, T. (2024). Detection of brain disorders using artificial neural networks. Journal of Autonomous Intelligence, 7(5), 704. https://doi.org/10.32629/jai.v7i5.704

[21] Khan, M. J., Akhtar, Md. N., Alam, A., & Afthanorhan, A. (2024). IoT based MPPT techniques for photovoltaic frameworks management under different environmental conditions: A review. International Journal of Informatics and Communication Technology (IJ-ICT), 13(2), 306. https://doi.org/10.11591/ijict.v13i2.pp306-313

[20] Khan, M. J., Akhtar, Md. N., & Afthanorhan, A. (2025). An innovative control of the charging and discharging for the battery management operation using a bidirectional converter. Future Technology, 4(1), 23–28. https://doi.org/10.55670/fpll.futech.4.1.3

[19] Khan, M. J., & Mathew, L. (2016). Different kinds of maximum power point tracking control method for photovoltaic systems: A review. Archives of Computational Methods in Engineering, 24(4), 855–867. https://doi.org/10.1007/s11831-016-9192-1

[18] Khan, M. J., Yadav, A. K., & Mathew, L. (2017). Techno economic feasibility analysis of different combinations of PV-Wind-Diesel-Battery hybrid system for telecommunication applications in different cities of Punjab, India. Renewable and Sustainable Energy Reviews, 76, 577–607. https://doi.org/10.1016/j.rser.2017.03.076

[17] Khan, M. J., & Mathew, L. (2019). Comparative study of maximum power point tracking techniques for hybrid renewable energy system. International Journal of Electronics, 106(8), 1216–1228. https://doi.org/10.1080/00207217.2019.1584917

[16] Khan, M. J., & Mathew, L. (2018). Comparative study of optimization techniques for renewable energy system. Archives of Computational Methods in Engineering, 27(2), 351–360. https://doi.org/10.1007/s11831-018-09306-8

[15] Khan, M. J., & Mathew, L. (2018). Comparative analysis of maximum power point tracking controller for wind energy system. International Journal of Electronics, 105(9), 1535–1550. https://doi.org/10.1080/00207217.2018.1461251

[14] Khan, M. J., & Mathew, L. (2018). Fuzzy logic controller-based MPPT for hybrid photo-voltaic/wind/fuel cell power system. Neural Computing and Applications, 31(10), 6331–6344. https://doi.org/10.1007/s00521-018-3456-7

[13] Khan, M. J. (2020). Review of recent trends in optimization techniques for hybrid renewable energy system. Archives of Computational Methods in Engineering, 28(3), 1459–1469. https://doi.org/10.1007/s11831-020-09424-2

[12] Khan, M. J., & Pushparaj. (2021). A novel hybrid maximum power point tracking controller based on artificial intelligence for solar photovoltaic system under variable environmental conditions. Journal of Electrical Engineering & Technology, 16(4), 1879–1889. https://doi.org/10.1007/s42835-021-00734-4

[11] Khan, M. J., & Mathew, L. (2021). Artificial neural network-based maximum power point tracking controller for real-time hybrid renewable energy system. Soft Computing, 25(8), 6557–6575. https://doi.org/10.1007/s00500-021-05653-0

[10] Khan, M. J. (2022). An AIAPO MPPT controller based real time adaptive maximum power point tracking technique for wind turbine system. ISA Transactions, 123, 492–504. https://doi.org/10.1016/j.isatra.2021.06.008

[9] Khan, M. J., Mathew, L., Alotaibi, M. A., Malik, H., & Nassar, M. E. (2022). Fuzzy-Logic-Based comparative analysis of different maximum power point tracking controllers for hybrid renewal energy systems. Mathematics, 10(3), 529. https://doi.org/10.3390/math10030529

[8] Khan, M. J., Kumar, D., Narayan, Y., Malik, H., García Márquez, F. P., & Gómez Muñoz, C. Q. (2022). A novel artificial intelligence maximum power point tracking technique for integrated PV-WT-FC frameworks. Energies, 15(9), 3352. https://doi.org/10.3390/en15093352

[7] Khan, M. J., Kumar, D., Narayan, Y., Malik, H., García Márquez, F. P., & Gómez Muñoz, C. Q. (2022). A novel artificial intelligence maximum power point tracking technique for integrated PV-WT-FC frameworks. Energies, 15(9), 3352. https://doi.org/10.3390/en15093352

[6] Mustafa, R., Agrawal, S., & Khan, M. J. (2022). Adaptive fusion based clustering approach in cognitive radio networks. Results in Control and Optimization, 8, 100147. https://doi.org/10.1016/j.rico.2022.100147

[5] Choudhary, A., Kumar, R., Letha, S. S., Bakhsh, F. I., Singh, A., & Khan, M. J. (2024a). Review of recent trends of advancements in multilevel inverter topologies with reduced power switches and control techniques. IET Power Electronics, 17,. https://doi.org/10.1049/pel2.12564

[4] Karad, S. G., Thakur, R., Alotaibi, M. A., Khan, M. J., Malik, H., Márquez, F. P. G., & Hossaini, M. A. (2024). Optimal design of fractional order vector controller using hardware-in-loop (HIL) and Opal RT for wind energy system. IEEE Access, 12, 35033–35047. https://doi.org/10.1109/access.2024.3357504

[3] Khan, M. J., Akhtar, M. N., Hasan, M., Malik, H., Ansari, M. F., & Afthanorhan, A. (2024). ANN-based maximum power point tracking technique for PV power management under variable conditions. International Journal of Mathematical, Engineering and Management Sciences, 9(5), 1106–1123. https://doi.org/10.33889/ijmems.2024.9.5.058

[2] Khan, M. J., Narayan, Y., Pawan, Afthanorhan, A., & Ilahi Bakhsh, F. (2025). Modified adaptive fuzzy logic based real-time MPPT controller for fuel cell framework management under dynamic conditions. Engineering Research Express, 7(2), 025317. https://doi.org/10.1088/2631-8695/adca86

[1] Pareek, S., Ansari, M. F., Khurana, N., Nezami, Md. M., Alharbi, S. S., Alharbi, S. S., Krishan, G., Dahiya, R., & Khan, M. J. (2025). Performance comparison of interconnection schemes for mitigating partial shading losses in solar photovoltaic arrays. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-12984-7