Subject Areas : Electrical Engineering

Maryam Goodarzian ¹ , Mohammad Reza Yousefi ² , Neda Behzadfar ³

1 - Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
2 - Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
3 - Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

Received: 2022-09-16 Accepted : 2022-12-30 Published : 2022-12-01

Keywords:

References:

[1]   M. Dorvashi, N. Behzadfar, G. Shahgholian, “Classification of alcoholic and non-alcoholic individuals based on frequency and non-frequency features of electroencephalogram signal”, Journal Iranian Journal of Biomedical Engineering, vol. 14, no. 2, pp. 121-130, Sum. 2020.

[2]   N. Behzadfar, “A brief overview on analysis and feature extraction of electroencephalogram signals”, Signal Processing and Renewable Energy, vol. 6, no. 1, pp. 39-64, 2022.

[3]   S. Liu, W. Wei, G. Ding, J. Ke, F. Hong, M. Tian, “Relationshipbetween depth of anesthesiaand effect-siteconcentration of propofol during induction with thetarget-controlled infusion technique in elderlypatients”, Chinese Medical Journal, vol. 122, no.8, pp. 935-940, 2009.

[4]   M. Lotfi-Forushani, B. Karimi, G. Shahgholian, “Optimal PID controller tuning for multivariable aircraft longitudinal autopilot based on particle swarm optimization algorithm”, Journal of Intelligent Proced­ures in Electrical Technology, vol. 3, no. 9, pp. 41-50, June 2012.

[5]   B. Ahmadzade, G. Shahgholian, F. M. Tehrani, M. Mahdavian, "Model predictive control to improve power system oscillations of SMIB with fuzzy logic controller", Proceeding of the IEEE/ICEMS, pp. 1-5,  Beijing, China, Aug. 2011

[6]   F. Doctor, H. Hagras, V. Callaghan, “A type-2 fuzzy embedded agent to realizeambient intelligence in ubiquitous computing environ­ments”, Information Sciences, vol. 171, no. 4, pp. 309–334, 2005.

[7]   M. Babaei, S.R.N. Kalhori, S. Sheybani, H. Karim, “A fuzzy rule-based expert system to determine propofol drug dosage in anesthesia”, Frontiers in Health Informatics, vol. 10, Article Number: 89, 2021.

[8]   S.P. Arunachalam, S. Kapa, S.K. Mulpuru, P.A. Friedman, E.G. Tolkacheva, “Intelligent fractional-order PID (FOPID) heart rate controller for cardiac pacemaker”, Proceeding of the IEEE/HI-POCT, pp. 105-108, Cancun, Mexico, 2016.

[9]   J.J. Hsu, J.I. Wang, A. Lee, D.Y. Li, C.H. Chen, S. Huang, A. Liu, B.K. Yoon, S.K. Kim, T.J. Tsai, “Automated control of blood glucose in the OR and surgical ICU”, Proceeding of the IEEE/EMBS, pp. 1286–1289, Minneapolis, MN, USA, 2009.

[10]           M. Denai, M. Mahfouf, J. Ross, “A fuzzy decision support system for therapy administration in cardiovascular intensive care patients”, Proceeding of the IEEE/IFSC, pp. 1-6, London, UK, 2007.

[11]           D.S. Diwase, R.W. Jasutkar, “Expert controller for estimating dose of isoflurane”, International Journal of Advanced Engineering Sciences and Technologies, vol. 9, no. 2, pp. 218-221, 2011.

[12]           D.P. Zaharieva, L.H. Messer, B. Paldus, D.N. O’Neal, D.M. Maahs, M.C. Riddell, “Erratum to glucose control during physical activity and exercise using closed loop technology in adults and adolescents with type 1 diabetes”, Canadian Journal of Diabetes, vol. 45, no. 1. Article Number: 96, 2021.

[13]           T. Chidentree, U. Sermsak, “Biological systems drug in fusion controller using FREN with sliding bounds”, IEEE Trans. Biomed. Eng, vol. 53, pp. 2405–2408, 2015

[14]           M.E. Karar, M.A. El-Brawany, “Automated cardiac drug infusion system using adaptive fuzzy neural networks controller”, B­i­om­edi­cal Engin­eering and Computational Biology, vol. 3, pp. 1–11, Jan. 2011.

[15]           L. Merigo, N. Latronico, F. Padula, M. Paltenghi, M. Schiavo, A. Visioli, "Optimization-based design of closed-loop control of anesthesia", Automated Drug Delivery in Anesthesia, pp. 233-267, 2020.

[16]           N. Jamali, A. Sadegheih, M. M. Lotfi, L. C. Wood, M. J. Ebadi, "Estimating the depth of anesthesia during the induction by a novel adaptive neuro-fuzzy inference system: A case study", Neural Processing Letters, vol. 53, no. 1, pp. 131-175, 2021.

[17]           Y. Tian, Z. Chu, and G. Ma, "Fuzzy logic control theory in clinical anesthesia", Expert Systems, vol. 39, no. 3, Article Number: e12761, March 2022.

[18]           M. Schiavo, F. Padula, N. Latronico, M. Paltenghi, and A. Visioli, "Individualized PID tuning for maintenance of general anesthesia with propofol", IFAC-PapersOnLine, vol. 54, no. 3, pp. 679-684, Jan. 2022.

[19]           S. Chakravarty, A. S. Waite, J. H. Abel, and E. N. Brown, "A simulation-based comparative analysis of PID and LQG control for closed-loop anesthesia delivery", IFAC-PapersOnLine, vol. 53, no. 2, pp. 15898-15903, 2020.

[20]           E. Hosseini, G. Shahgholian, H. Mahdavi-Nasab, F. Mesrinejad, “Variable speed wind turbine pitch angle control using three-term fuzzy controller”, International Journal of Smart Electrical Engineering, vol. 11, no. 2, pp. 63-70, June 2022.

[21]           S. Nasr, H. Mahmoodian, “Insulin drug regulation by general type 2 fuzzy controller with alpha plane”, Journal of Intelligent Procedures in Electrical Technology, vol. 10, no. 37, pp. 39-48, 2019.

[22]           S. Dequan, G. Guili, G. Zhiwei, X. Peng, “Application of expert fuzzy PID method for temperature control of heating furnace”, Procedia Engineering, vol. 29, pp. 257-261, 2012.

[23]           H. Huang, S. Zhang, Z. Yang, Y. Tian, X. Zhao, Z. Yuan, S. Hao, J. Leng, Y. Wei, “Modified Smith fuzzy PID temperature control in an oil-repleni­shing device for deep-sea hydraulic system”, Ocean Engineering, vol. 149, pp. 14-22, 2018.

[24]           G. Shahgholian, M. Maghsoodi, M. Mahdavian, M. Janghorbani, M. Azadeh, S. Farazpey, "Analysis of speed control in DC motor drive by using fuzzy control based on model reference adaptive control", Proceeding of the IEEE/ECTI-CON, pp. 1-6, Chiang Mai, Thailand, June/July 2016, doi: 10.1109/ECTICon.2016.7561239.

[25]           F. Hedarpour, G. Shahgholian, "Design and simulation of sliding and fuzzy sliding mode controller in hydro-turbine governing system", Journal of Iranian Dam and Hedroelectric Powerplant, vol. 4, no. 12, pp. 10-20, Aug. 2017.

[26]           M. R. Yousefi, S. Hasanzadeh, H. Mirinejad, M. Ghasemian, "A hybrid neuro-fuzzy approach for greenhouse climate modeling", Proceeding of the IEEE/ICIS, pp. 212-217, London, UK, July 2010, doi: 10.1109/IS.2010.5548375.

[27]           M Montazeri, M.R. Yousefi, K. Shojaei, G. Shahgholian, “Fast adaptive fuzzy terminal sliding mode control of synergistic movement of the hip and knee joints (air-stepping) using functional electrical stimulation: A simulation study”, Biomedical Signal Processing and Control, vol. 66, Article Number: 102445, 2021.