Abstract
In recent times, the intelligent biological control system in biomedical engineering has been utilized in various applications such as prosthesis control, drug delivery control, blood glucose control, and heart rate regulation. Moreover, the pancreas, gene regulatory network (GRN), and protein are the main sources in the human body system. However, the parameter regulations of these systems are crucial, because the conventional control methods lack the finest performance, provoking a lot of errors. With an advanced control method, the parameters of the biological system can regulate as per the level to avoid serious conditions. Therefore, in this research, a novel self-constructing intelligent emperor penguin (SIEP) algorithm based fractional-order adaptive proportional integral derivative (FAPID) controller is proposed to regulate the parameters of the system. Here, the FAPID controller gain parameters are effectively tuned by the SIEP algorithm. This proposed SIEP-FAPID controller regulates the constraints of linear time-invariant (LTI) based biological systems such as the pancreas, GRN, and protein formation as per the required level. Moreover, the stability of the controller is studied using the discrete Lyapunov stability analysis function. The quality of the control function has been improved using this proposed approach thus the finest gain and reduced error percentage was obtained. Furthermore, the proposed simulation outcomes are compared with various conventional control approaches which are validated for proving the enhanced controller function under external disturbances. The comparison shows that the proposed SIEP algorithm in the FAPID controller has attained 0.1% less error while comparing with the existing controllers.
Similar content being viewed by others
References
Precup R, Teban T, Albu A, Borlea A, Zamfirache IA, Petriu EM (2020) Evolving fuzzy models for prosthetic hand myoelectric-based control. IEEE Trans Instrum Meas 69(7):4625–4636. https://doi.org/10.1109/TIM.2020.2983531
Xu J, Guo K, Menchinelli F, Park SH (2019) Eye fixation location recommendation in advanced driver assistance system. J Electr Eng Technol 14:965–978. https://doi.org/10.1007/s42835-019-00091-3
Jafri, S.R.u.N., Jamshaid, A., Jafri, S.M.u.N., & Iqbal, J. (2020) Estimation of surgical needle insertion force using Kalman filter. J Electr Eng Technol 15:899–906. https://doi.org/10.1007/s42835-020-00355-3
Franco R, de Loza AF, Ríos H, Cassany L, Gucik-Derigny D, Cieslak J, Henry D, Olçomendy L (2021) Output-feedback sliding-mode controller for blood glucose regulation in critically Ill patients affected by type 1 diabetes. IEEE Trans Control Syst Technol. https://doi.org/10.1109/TCST.2020.3046420
Lv L, Wang S, Huang S, Hei X, Yang Y (2019) A novel identification approach for palm bio-impedance spectroscopy. J Electr Eng Technol 14:2105–2116. https://doi.org/10.1007/s42835-019-00138-5
Moscoso-Vasquez M, Colmegna P, Rosales N, Garelli F, Sanchez-Pena R (2020) Control-oriented model with intra-patient variations for an artificial pancreas. IEEE J Biomed Health Inform 24(9):2681–2689. https://doi.org/10.1109/JBHI.2020.2969389
Zang H, Zhang T, Zhang Y (2015) Bifurcation analysis of a mathematical model for genetic regulatory network with time delays. Appl Math Comput 260:204–226. https://doi.org/10.1016/j.amc.2015.03.041
Li D, Zhang S, Ma X (2021) Dynamic module detection in temporal attributed networks of cancers. IEEE/ACM Trans Comput Biol Bioinf. https://doi.org/10.1109/TCBB.2021.3069441
Pan W, Wang Z, Gao H, Li Y (2010) Robust H∞ feedback control for uncertain stochastic delayed genetic regulatory networks with additive and multiplicative noise. Int J Robust Nonlinear Control 20(18):2093–2107. https://doi.org/10.1002/rnc.1571
Pereira B, Billaud M, Almeida R (2017) RNA-binding proteins in cancer: old players and new actors. Trends in Cancer 3(7):506–528. https://doi.org/10.1016/j.trecan.2017.05.003
Whitby M, Cardelli L, Kwiatkowska M, Laurenti L, Tribastone M, Tschaikowski M (2021) PID control of biochemical reaction networks. IEEE Trans Autom Control. https://doi.org/10.1109/TAC.2021.3062544
Bober JR, Beisel CL, Nair NU (2018) Synthetic biology approaches to engineer probiotics and members of the human microbiota for biomedical applications. Annu Rev Biomed Eng 20:277–300. https://doi.org/10.1146/annurev-bioeng-062117-121019
Hewing L, Wabersich KP, Menner M (2020) Learning-based model predictive control: toward safe learning in control. Ann Rev Control Robot Auton Syst 3:269–296. https://doi.org/10.1146/annurev-control-090419-075625
Revathi S, Radhakrishnan TK, Sivakumaran N (2017) Climate control in greenhouse using intelligent control algorithms. In: 2017 American control conference (ACC), IEEE. https://doi.org/10.23919/ACC.2017.7963065
Khosravi M, Behrunani V, Myszkorowski P, Smith RS, Rupenyan A, Lygeros J (2021) Performance-driven cascade controller tuning with bayesian optimization. IEEE Trans Industr Electron. https://doi.org/10.1109/TIE.2021.3050356
Vanchinathan K, Valluvan KR (2018) A metaheuristic optimization approach for tuning of fractional-order PID controller for speed control of sensorless BLDC motor. J Circuits Syst Comput 27(08):1850123. https://doi.org/10.1142/S0218126618501232
Mobayen S, Tchier F (2017) Nonsingular fast terminal sliding-mode stabilizer for a class of uncertain nonlinear systems based on disturbance observer. J Sci Islam Repub Iran 24(3):1410–1418
Bahremand S, Ko HS, Balouchzadeh R, Lee HF (2019) Neural network-based model predictive control for type 1 diabetic rats on artificial pancreas system. J Med Biol Eng 57(1):177–191. https://doi.org/10.1007/s11517-018-1872-6
Sharma R, Deepak KK, Gaur P, Joshi D (2020) An optimal interval type-2 fuzzy logic control based closed-loop drug administration to regulate the mean arterial blood pressure. Comput Methods Progr Biomed 185:105167. https://doi.org/10.1016/j.cmpb.2019.105167
Reboucas Filho PP, da Silva SPP, Praxedes VN (2019) Control of singularity trajectory tracking for robotic manipulator by genetic algorithms. J Comput Sci 30:55–64. https://doi.org/10.1016/j.jocs.2018.11.006
Saucedo JAM, Hemanth JD, Kose U (2019) Prediction of electroencephalogram time series with electro-search optimization algorithm trained adaptive neuro-fuzzy inference system. IEEE Access 7:15832–15844. https://doi.org/10.1109/ACCESS.2019.2894857
Paoletti N, Liu KS, Chen H, Smolka S (2019) Data-driven robust control for a closed-loop artificial pancreas. IEEE/ACM Trans Comput Biol Bioinf. https://doi.org/10.1109/TCBB.2019.2912609
Verdult V, Verhaegen M (2002) Subspace identification of multivariable linear parameter-varying systems. Automatica 38(5):805–814. https://doi.org/10.1016/S0005-1098(01)00268-0
Tao B, Xiao M (2017). PID control at bifurcation in a single-gene regulatory model with delays. In: IECON 2017–43rd annual conference of the IEEE industrial electronics society, IEEE. https://doi.org/10.1109/IECON.2017.8216891
Mairet F (2018) Abiomolecular proportional integral controller based on feedback regulations of protein level and activity. R Soc Open Sci 5(2):171966. https://doi.org/10.1098/rsos.171966
Ahmad I, Munir F, Munir MF (2019) An adaptive backstepping based non-linear controller for artificial pancreas in type 1 diabetes patients. Biomed Signal Process Control 47:49–56. https://doi.org/10.1016/j.bspc.2018.07.016
Acknowledgements
None.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no potential conflict of interest.
Statement of Animal and Human Rights
All applicable institutional and/or national guidelines for the care and use of animals were followed.
Informed Consent
For this type of analysis formal consent is not needed.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Balasaheb, W.V., Uttam, C. Novel Intelligent Optimization Algorithm Based Fractional Order Adaptive Proportional Integral Derivative Controller for Linear Time Invariant based Biological Systems. J. Electr. Eng. Technol. 17, 565–580 (2022). https://doi.org/10.1007/s42835-021-00874-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s42835-021-00874-7