CONTROLLING THE MEAN ARTERIAL PRESSURE BY MODIFIED MODEL REFERENCE ADAPTIVE CONTROLLER BASED ON TWO OPTIMIZATION ALGORITHMS
Rawaa HAAMED
engrawaa1990@gmail.comMustansiriyah University, Computer Engineering Department, Palestine Street, 14022, Baghdad (Iraq)
Ekhlas HAMEED
Mustansiriyah University, Computer Engineering Department, Palestine Street, 14022, Baghdad (Iraq)
Abstract
This paper Presents Modified Model Reference Adaptive Controller (MRAC) to regulate the hight blood pressure. It is based on slate model that represent the mathematical equation that clarifies relationship between blood pressure and vasoactive drug injection. In this work Squirrel Search Algorithm (SSA) and Grey Wolf Optimizer (GWO)algorithms are considered to optimize the controller parameters. the results showed that the suggested controller has good performance and stabilize the mean arterial pressure with small settling time (below than 400s) and small overshoot (below than 1 mmHg) with low amount of error.
Keywords:
Mean Arterial Pressure, Squirrel Search Algorithm, Model Reference Adaptive ControllerReferences
Basha, A.A., & Vivekanandan, S. (2019). Enhanced Optimal Insulin Regulation in Post-Operative Diabetic Patients: An Adaptive Cascade Control Compensation-Based Approach With Diabetic and Hypertension. IEEE Access, 7, 90973–90981. https://doi.org/10.1109/ACCESS.2019.2927248
DOI: https://doi.org/10.1109/ACCESS.2019.2927248
Google Scholar
Basha, A.A., Vivekanandan, S., & Parthasarathy, P. (2018). Evolution of blood pressure control identification in lieu of post-surgery diabetic patients: a review. Health Inf Sci Syst, 6, 17. https://doi.org/10.1007/s13755-018-0055-z
DOI: https://doi.org/10.1007/s13755-018-0055-z
Google Scholar
Cavalcanti, A.L., & Maitelli, A.L. (2015). Design of an Intelligent Adaptive Drug Delivery System for Arterial Pressure Control. WSEAS Transactions on Systems and Control, 10, 704–712.
Google Scholar
da Silva, S.J., Scardovelli, T.A., & da Silva Boschi, S.R.M. et al. (2019). Simple adaptive PI controller development and evaluation for mean arterial pressure regulation. Res. Biomed. Eng., 35, 157–165. https://doi.org/10.1007/s42600-019-00017-y
DOI: https://doi.org/10.1007/s42600-019-00017-y
Google Scholar
de Moura Oliveira, P.B., Durães, J., & Pires, E.J.S. (2014). Mean Arterial Pressure PID Control Using a PSO-BOIDS Algorithm. In: Á. Herrero, et al. (Eds.), International Joint Conference SOCO’13-CISIS’13-ICEUTE’13. Advances in Intelligent Systems and Computing (vol. 239). Springer, Cham
DOI: https://doi.org/10.1007/978-3-319-01854-6_10
Google Scholar
Enbiya, S., Mahieddine, F., & Hossain, A. (2011). Model reference adaptive scheme for multi-drug infusion for blood pressure control. J Integr Bioinform, 8(3), 173. https://doi.org/10.2390/biecoll-jib-2011-173
DOI: https://doi.org/10.1515/jib-2011-173
Google Scholar
Hu, H., Zhang, L., Bai, Y., Wang, P., & Tan, X. (2019). A Hybrid Algorithm Based on Squirrel Search Algorithm and Invasive Weed Optimization for Optimization. IEEE Access, 7, 105652–105668. https://doi.org/10.1109/ACCESS.2019.2932198
DOI: https://doi.org/10.1109/ACCESS.2019.2932198
Google Scholar
Jain, P., & Nigam, M.J. (2013). Design of a Model Reference Adaptive Controller Using Modified MIT Rule for a Second Order System. Adv. Electron. Electr. Eng., 3(4), 477–484.
Google Scholar
Jones, R.W., & Tham, M.T. (2005). An undergraduate CACSD project: The control of mean arterial blood pressure during surgery. Int. J. Eng. Educ., 21(6) PART I, 1043–1049.
Google Scholar
Khan, T.A., & Ling, S.H. (2020). An improved gravitational search algorithm for solving an electromagnetic design problem. J Comput Electron, 19, 773–779. https://doi.org/10.1007/s10825-020-01476-8
DOI: https://doi.org/10.1007/s10825-020-01476-8
Google Scholar
Ladaci, S. (2012). Postoperative Blood Pressure Control Using a Fractional order Adaptive Regulator. In 13th International conference on Sciences and Techniques of Automatic control & computer engineering (pp. 254–265). Monastir, Tunisia.
Google Scholar
Malagutti, N. (2014). Particle filter-based robust adaptive control for closed-loop administration of sodium nitroprusside. J Comput Surg, 1, 8. https://doi.org/10.1186/2194-3990-1-8
DOI: https://doi.org/10.1186/2194-3990-1-8
Google Scholar
Malagutti, N., Dehghani, A., & Kennedy, R.A. (2013). Robust control design for automatic regulation of blood pressure. IET Control Theory Appl., 7(3), 387–396. http://dx.doi.org/10.1049/iet-cta.2012.0254
DOI: https://doi.org/10.1049/iet-cta.2012.0254
Google Scholar
Mirjalili, S., Mirjalili, S.M., & Lewis, A. (2014). Grey Wolf Optimizer. Adv. Eng. Softw., 69, 46–61.
DOI: https://doi.org/10.1016/j.advengsoft.2013.12.007
Google Scholar
Nirmala, S.A., Muthu, R., & Abirami, B.V. (2013). Drug infusion control for mean arterial pressure regulation of critical care patients. In 2013 IEEE International Conference of IEEE Region 10 (TENCON 2013) (pp. 1-4). Xi'an. https://doi.org/10.1109/TENCON.2013.6718882.
DOI: https://doi.org/10.1109/TENCON.2013.6718882
Google Scholar
Precup, R.-E., David, R.-C., Szedlak-Stinean, A.-I., Petriu, E.M., & Dragan, F. (2017). An Easily Understandable Grey Wolf Optimizer and Its Application to Fuzzy Controller Tuning. Algorithms, 10, 68.
DOI: https://doi.org/10.3390/a10020068
Google Scholar
Saeed Al-Khayyt, S. (2017). Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking. Al-Khwarizmi Engineering Journal, 9(1), 19-28.
Google Scholar
Saxena, S., & Hote, Y.V. (2012). A simulation study on optimal IMC based PI/PID controller for mean arterial blood pressure. Biomed. Eng. Lett., 2, 240–248. https://doi.org/10.1007/s13534-012-0077-4
DOI: https://doi.org/10.1007/s13534-012-0077-4
Google Scholar
Silva, H.A., Leão, C.P., & Seabra, E.A. (2018). Parametric Sensitivity Analysis of a Multiple Model Adaptive Predictive Control for Regulation of Mean Arterial Blood Pressure. In Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2018) (vol. 1, 510–516). http://dx.doi.org/10.5220/0006909805100516
DOI: https://doi.org/10.5220/0006909805100516
Google Scholar
Singh, B., & Urooj, S. (2019). Blood pressure control by deterministic learning based fuzzy logic control. Int. J. Eng. Adv. Technol., 8(3), 6–10.
Google Scholar
Slate, J.B., & Sheppard, L.C. (1983). Model-Based Adaptive Blood Pressure Controller. IFAC Proc. Vol., 2(4), 1437–1442.
DOI: https://doi.org/10.1016/S1474-6670(17)63200-2
Google Scholar
Urooj, S., & Singh, B. (2019). Fractional-order PID control for postoperative mean arterial blood pressure control scheme. Procedia Comput. Sci., 152, 380–389. https://doi.org/10.1016/j.procs.2019.05.002
DOI: https://doi.org/10.1016/j.procs.2019.05.002
Google Scholar
Authors
Rawaa HAAMEDengrawaa1990@gmail.com
Mustansiriyah University, Computer Engineering Department, Palestine Street, 14022, Baghdad Iraq
Authors
Ekhlas HAMEEDMustansiriyah University, Computer Engineering Department, Palestine Street, 14022, Baghdad Iraq
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