Development of Adaptive PD Control for Infant Incubator Using Fuzzy Logic

Abd Kholiq, Lamidi Lamidi, Farid Amrinsani, Triwiyanto Triwiyanto, Hafizh Aushaf Mahdy, Ragimova Nazila, Vugar Abdullayev

Abstract


This research aims to design an innovative fuzzy logic auto-tuning PD algorithm to control the temperature in a baby Incubator. The proposed Fuzzy-PD method combines fuzzy logic with PD control using the Arduino Mega 2560 microcontroller. The Proportional and Derivative parameters are adjusted by fuzzy logic based on feedback of error values and rate of change of error. The temperature setting range used in data collection is 32-37°C. When the temperature setting is higher, the time required to reach the specified temperature setting becomes longer. The overshoot tends to be low, as the system is designed to respond to temperature changes with high precision. The temperature inside the baby Incubator can be maintained with a low steady-state error value. The adaptive fuzzy-PD system can restore the temperature inside the baby Incubator to the set temperature after a disturbance. Compared to the x device, the average error value is 0.0013%. Independent sample t-tests show no significant difference between the baby Incubator and the Incu analyzer device. It can be concluded that the combination of fuzzy logic and PD control system works well in maintaining temperature stability with low error values. The results are better than previous research focusing on designing a PD algorithm with a maximum rise time of 480 seconds. Furthermore, there is potential for further development with a fuzzy logic auto-tuning PID algorithm to achieve better results.

Keywords


Baby Incubator; Auto Tuning; Fuzzy Logic; PD Controller; Fuzzy-PD.

Full Text:

PDF

References


I. S. Mustikawati, H. Pratomo, E. Martha, and A. I. Murty, “Knowledge, Attitude, and Practice using the Kangaroo Method Care in Maternal with Low Birth Weight Babies,” Kemas, vol. 17, no. 3, pp. 436–443, 2022, doi: 10.15294/kemas.v17i3.29548.

R. A. Abdo, H. M. Halil, M. A. Muhammed, and M. S. Karebo, “Magnitude of Preterm Birth and Its Associated Factors: A Cross-Sectional Study at Butajira Hospital, Southern Nations, Nationalities, and People’s Region, Ethiopia,” International Journal of Pediatrics, vol. 2020, 2020, doi: 10.1155/2020/6303062.

J. S. Machado, T. S. Ferreira, R. C. G. Lima, V. C. Vieira, and D. S. de Medeiros, “Premature birth: Topics in physiology and pharmacological characteristics,” Revista da Associacao Medica Brasileira, vol. 67, no. 1, pp. 150–155, 2021, doi: 10.1590/1806-9282.67.01.20200501.

B. Riadl, H. Youcef, M. Mohammed, and M. Elarkam, “Particle Swarm Optimization for tuning a Fuzzy Supervisory Controller Parametesrs (Takagi Seguno and Mamdani Engines),” Algerian Journal of Signals and Systems, vol. 5, no. 2, pp. 92-97, 2020.

A. V. Zaelani, R. A. Koestoer, I. Roihan, and Harinaldi, “Analysis of temperature stabilization in grashof incubator with environment variations based on Indonesian national standard (SNI),” in AIP Conference Proceedings, vol. 2062, no. 1, 2019.

T. T. Ngo, C. C. Wang, Y. T. Chen, and V. T. Than, “Developing a thermoelectric cooling module for control temperature and thermal displacement of small built-in spindle,” Thermal Science and Engineering Progress, vol. 25, Oct. 2021.

V. Nekoukar and N. Mahdian Dehkordi, “Robust path tracking of a quadrotor using adaptive fuzzy terminal sliding mode control,” Control Eng Pract, vol. 110, May 2021.

M. Doosthosseini et al., "Monitoring, Control System Development, and Experimental Validation for a Novel Extrapulmonary Respiratory Support Setup," in IEEE/ASME Transactions on Mechatronics, vol. 27, no. 5, pp. 4177-4187, Oct. 2022.

N. Nasimsha, G. M. Kumar, T. Rajalakshmi, and E. R. Gafoor, “Automated Cradle with Incubator for Infants,” Biomed. Eng., vol. 32, no. 5, Oct. 2020, doi: 10.4015/S1016237220500374.

P. T. Kapen, Y. Mohamadou, F. Momo, D. K. Jauspin, and G. Anero, “An energy efficient neonatal incubator: mathematical modeling and prototyping,” Health Technol., vol. 9, no. 1, pp. 57–63, Jan. 2019.

Z. Gao, Y. Liu, and Z. Wang, “On Stabilization of Linear Switched Singular Systems via P-D State Feedback,” IEEE Access, vol. 8, pp. 97007–97015, 2020, doi: 10.1109/ACCESS.2020.2996687.

T. Shiota and H. Ohmori, “Design of adaptive I-PD control system with variable reference model,” in 2013 Australian Control Conference, pp. 115–120, 2013, doi: 10.1109/AUCC.2013.6697258.

P. Chen and Y. Luo, “A Two-Degree-of-Freedom Controller Design Satisfying Separation Principle With Fractional-Order PD and Generalized ESO,” IEEE/ASME Transactions on Mechatronics, vol. 27, no. 1, pp. 137–148, Feb. 2022.

P. S. Mahardika and A. A. N. Gunawan, “Modeling of water temperature in evaporation pot with 7 Ds18b20 sensors based on Atmega328 microcontroller,” Linguistics and Culture Review, vol. 6, pp. 184–193, Jan. 2022, doi: 10.21744/lingcure.v6ns3.2123.

R. A. Koestoer, Y. A. Saleh, I. Roihan, and Harinaldi, “A simple method for calibration of temperature sensor DS18B20 waterproof in oil bath based on Arduino data acquisition system,” in AIP Conference Proceedings, vol. 2062, no. 1, 2019, doi: 10.1063/1.5086553.

W. Widhiada, I. N. G. Antara, I. N. Budiarsa, and I. M. G. Karohika, “The Robust PID Control System of Temperature Stability and Humidity on Infant Incubator Based on Arduino at Mega 2560,” in IOP Conference Series: Earth and Environmental Science, vol. 248, no. 1, p. 012046, 2019, doi: 10.1088/1755-1315/248/1/012046.

Z. Hu, F. Chen, R. Shen, and S. Li, “Design and implementation of forest fire monitoring system based on internet of things technology,” ITM Web of Conferences, vol. 45, p. 01063, 2022.

S. Halder, A. Khan, U. N. Thakur, and S. Saha, “Design and Analysis of Temperature Control System using Conventional PI and Advanced ANN Controllers,” in 2018 International Conference on Computing, Power and Communication Technologies (GUCON), pp. 4–8, 2018.

S. Y. Ismail, Z. S. Hussain, H. T. H. H. Thabet, and T. H. Thabit, “Using PI Controller Unit for Controlling the Water Temperature in Oil Fired Heaters by PLC Techniques,” Przeglad Elektrotechniczny, vol. 97, no. 3, pp. 157–161, 2021, doi: 10.15199/48.2021.03.30.

T. A. Tisa, Z. A. Nisha, and M. A. Kiber, “Design Of An Enhanced Temperature Control System For Neonatal Incubator,” Bangladesh Journal of Medical Physics, vol. 5, no. 1, pp. 53-61, 2012.

J. A. D. Pinto, E. Á. Córdova, and C. B. C. Lévano, “Design and Implementation of a Digital PID Temperature Controller for Neonatal Incubator ESVIN,” Journal of Mechanics Engineering and Automation, vol. 5, no. 3, Mar. 2015.

M. A. Popoola, B. Ohaeri, I. O. Ojo, and O. Babarimisa, “Preterm Birth, Prevention, Prediction, Care,” European Journal of Medical and Health Sciences, vol. 5, no. 1, pp. 6–10, Jan. 2023.

A. Kholiq and Lamidi, “Analysis of Temperature Sensors with Proportional and Derivative Controls Applied to Infant Incubators,” Journal of Biomimetics, Biomaterials and Biomedical Engineering, vol. 55, pp. 216–225, 2022, doi: 10.4028/p-f9uc3z.

S. I. Tomashevich, A. L. Fradkov, B. Andrievsky, A. O. Belyavskyi, and K. Amelin, “Simple adaptive control of quadrotor attitude. Algorithms and experimental results,” in 2017 25th Mediterranean Conference on Control and Automation (MED), pp. 933–938, 2017.

R. Mondal and J. Dey, “A novel design methodology on cascaded fractional order (FO) PI-PD control and its real time implementation to Cart-Inverted Pendulum System,” ISA Trans, vol. 130, pp. 565–581, Nov. 2022, doi: 10.1016/j.isatra.2022.04.015.

T. Liu and Z. Nie, “PD-Based Iterative Learning Control for the Nonlinear Low-Speed-Jitter Vibration of a Wind Turbine in Yaw Motion,” Applied Sciences, vol. 14, no. 5, p. 1750, Feb. 2024.

A. J. Abougarair, “Model Reference Adaptive Control and Fuzzy Optimal Controller for Mobile Robot,” Journal of Multidisciplinary Engineering Science and Technology, vol. 6, no. 3, pp. 9722-9728 2019.

V. Kumar, B. C. Nakra, and A. P. Mittal, “A Review on Classical and Fuzzy PID Controllers,” International Journal of Intelligent Control and Systems, vol. 16, no. 3, pp. 170-181, 2011.

Q. Li and D. Shen, “A New Incremental Fuzzy PD+Fuzzy ID Fuzzy Controller,” in 2009 WASE International Conference on Information Engineering, pp. 615–619, 2009, doi: 10.1109/ICIE.2009.271.

A. Kasbi and A. Rahali, “Performance optimization of doubly-fed induction generator (DFIG) equipped variable-speed wind energy turbines by using three-level converter with adaptive fuzzy PI control system,” in Materials Today: Proceedings, pp. 2648–2656, 2021.

D. Chen and D. E. Seborg, “PI/PID Controller Design Based on Direct Synthesis and Disturbance Rejection,” Ind Eng Chem Res, vol. 41, no. 19, pp. 4807–4822, Sep. 2002, doi: 10.1021/ie010756m.

I. Kaya and F. Peker, “Optimal I-PD controller design for setpoint tracking of integrating processes with time delay,” IET Control Theory and Applications, vol. 14, no. 18, pp. 2814–2824, Dec. 2020.

J. Lu, G. Chen, and H. Ying, “Predictive fuzzy PID control: theory, design and simulation,” Inf. Sci., vol. 137, no. 1–4, pp. 157–187, Sep. 2001, doi: 10.1016/S0020-0255(01)00119-0.

O. Saleem and K. Mahmood-ul-Hasan, “Robust stabilisation of rotary inverted pendulum using intelligently optimised nonlinear self-adaptive dual fractional-order PD controllers,” Int. J. Syst. Sci., vol. 50, no. 7, pp. 1399–1414, May 2019.

S. W. Sung, J. Lee, and I. Lee, Process Identification and PID Control. Wiley, 2009, doi: 10.1002/9780470824122.

H. Li, H. Sun, and L. Hou, “Adaptive Fuzzy PI Prescribed Performance Tracking Control for Switched Nonlinear Systems with Dead-Zone Input and External Disturbances,” IEEE Access, vol. 8, pp. 143938–143949, 2020, doi: 10.1109/ACCESS.2020.3013939.

V. C. Kirana, D. H. Andayani, A. Pudji, and A. Hannouch, “Effect of Closed and Opened the Door to Temperature on PID-Based Baby Incubator with Kangaroo Mode,” Indonesian Journal of electronics, electromedical engineering, and medical informatics, vol. 3, no. 3, pp. 121–127, Aug. 2021, doi: 10.35882/ijeeemi.v3i3.6.

M. Irshad and A. Ali, “Robust PI-PD controller design for integrating and unstable processes,” in IFAC-PapersOnLine, pp. 135–140, 2020.

M. Abdulgader and D. Kaur, “Evolving Mamdani Fuzzy Rules Using Swarm Algorithms for Accurate Data Classification,” IEEE Access, vol. 7, pp. 175907–175916, 2019, doi: 10.1109/ACCESS.2019.2957735.

A. Yunan and M. Ali, “Study and Implementation of the Fuzzy Mamdani and Sugeno Methods in Decision Making on Selection of Outstanding Students at the South Aceh Polytechnic,” Jurnal Inotera, vol. 5, no. 2, pp. 152–164, Nov. 2020.

B. M. Mohan and A. Sinha, “The simplest fuzzy two-term controllers: mathematical models and stability analysis,” International Journal of Automation and Control, vol. 2, no. 1, p. 5, 2008.

L. Zhang, B. Li, H. Du, and B. Zhang, “Takagi-Sugeno Fuzzy-based Kalman Filter Observer for Vehicle Side-slip Angle Estimation and Lateral Stability Control,” in 3rd International Symposium on Autonomous Systems, ISAS 2019, pp. 352–357, 2019, doi: 10.1109/ISASS.2019.8757751.

P. Dutta and N. Anjum, “Optimization of Temperature and Relative Humidity in an Automatic Egg Incubator Using Mamdani Interference System,” 2021 2nd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), pp. 12-16, 2022, doi: 10.1109/ICREST51555.2021.9331155.

N. M. Raharja, I. Suwarno, and Sugiyarta, “Current Trends in Incubator Control for Premature Infants with Artificial Intelligence Based on Fuzzy Logic Control: Systematic Literature Review,” Journal of Robotics and Control (JRC), vol. 3, no. 6, pp. 863–877, Nov. 2022, doi: 10.18196/jrc.v3i6.13341.

Y. Liu, Q. Zhu, and L. Wang, “Event-based adaptive fuzzy control design for nonstrict-feedback nonlinear time-delay systems with state constraints,” ISA Trans, vol. 125, pp. 134–145, Jun. 2022.

T. Takagi and M. Sugeno, “Fuzzy Identification of Systems and Its Applications to Modeling and Control,” IEEE transactions on systems, man, and cybernetics, no. 1, pp. 116-132, 1985, doi: 10.1109/TSMC.1985.6313399.

T. Zhao, C. Chen, H. Cao, S. Dian, and X. Xie, “Multiobjective Optimization Design of Interpretable Evolutionary Fuzzy Systems With Type Self-Organizing Learning of Fuzzy Sets,” IEEE Transactions on Fuzzy Systems, vol. 31, no. 5, pp. 1638–1652, May 2023, doi: 10.1109/TFUZZ.2022.3207318.

I. Birou, V. Maier, S. Pavel, and C. Rusu, “Indirect vector control of an induction motor with fuzzy-logic based speed controller,” Advances in Electrical and Computer Engineering, vol. 10, no. 1, pp. 116-120, 2010.

C. C. Lee, “Fuzzy logic in control systems: fuzzy logic controller. I,” IEEE Transactions on systems, man, and cybernetics, vol. 20, no. 2, pp. 404-418, 1990.

I. Eker and Y. Torun, “Fuzzy logic control to be conventional method,” Energy Convers. Manag., vol. 47, no. 4, pp. 377–394, Mar. 2006, doi: 10.1016/j.enconman.2005.05.008.

F. Furizal, S. Sunardi, and A. Yudhana, “Temperature and Humidity Control System with Air Conditioner Based on Fuzzy Logic and Internet of Things,” Journal of Robotics and Control (JRC), vol. 4, no. 3, pp. 308–322, May 2023, doi: 10.18196/jrc.v4i3.18327.

E. Mujčić and U. Drakulić, “Design and implementation of fuzzy control system for egg incubator based on IoT technology,” IOP Conf Ser. Mater. Sci. Eng., vol. 1208, no. 1, p. 012038, Nov. 2021, doi: 10.1088/1757-899X/1208/1/012038.

P. Singhala, D. Shah, and B. Patel, “Temperature Control using Fuzzy Logic,” International Journal of Instrumentation and Control Systems, vol. 4, no. 1, pp. 1–10, Jan. 2014, doi: 10.5121/ijics.2014.4101.

V. Chitra and R. S. Prabhakar, “Induction Motor Speed Control using Fuzzy Logic Controller,” World Academy of Science, Engineering and Technology, vol. 23, no. 2006, pp. 17-22, 2006.

Y. Shi, Z. Qiao, K. Bai, G. Chen, and Z. Liu, “A fuzzy adaptive PID control algorithm with improved quantification factor,” in Journal of Physics: Conference Series, vol. 1828, no. 1, p. 012154, 2021, doi: 10.1088/1742-6596/1828/1/012154.

H. Yuan, H. Dai, W. Wu, J. Xie, J. Shen, and X. Wei, “A fuzzy logic PI control with feedforward compensation for hydrogen pressure in vehicular fuel cell system,” Int. J. Hydrogen Energy, vol. 46, no. 7, pp. 5714–5728, Jan. 2021, doi: 10.1016/j.ijhydene.2020.11.089.

M. J. Patyra, J. L. Grantner, and K. Koster, “Digital Fuzzy Logic Controller: Design and,” IEEE Transactions on Fuzzy Systems, vol. 4, no. 4, pp. 439-459, 1996.

A. Arostegui, D. S. Benitez, and L. Caiza, “A Fuzzy-PD controller optimized by artificial bee colony algorithm applied to a small-scale pasteurization plant,” in 2020 IEEE ANDESCON, pp. 1-6, 2020, doi: 10.1109/ANDESCON50619.2020.9272184.

I. H. Altas and A. M. Sharaf, “A Generalized Direct Approach For Designing Fuzzy Logic Controllers In Matlab/Simulink Gui Environment,” International journal of information technology and intelligent computing, vol. 1, no. 4, pp. 1-27, 2007.

S. Sharma and A. J. Obaid, “Mathematical modelling, analysis and design of fuzzy logic controller for the control of ventilation systems using MATLAB fuzzy logic toolbox,” Journal of Interdisciplinary Mathematics, vol. 23, no. 4, pp. 843–849, May 2020, doi: 10.1080/09720502.2020.1727611.

S. Hrehova, J. Husár, and V. Hladký, “Possibility of using Matlab application to propose fuzzy computer model,” in IOP Conference Series: Materials Science and Engineering, vol. 1199, no. 1, p. 012020, 2021.

A. Fekik et al., “Adapted Fuzzy Fractional Order proportional-integral controller for DC Motor,” in Proceedings - 2020 1st International Conference of Smart Systems and Emerging Technologies, SMART-TECH 2020, pp. 1–6, 2020, doi: 10.1109/SMART-TECH49988.2020.00019.

Y. M. Alsayed, A. A. Abouelsoud, and F. A. M. R. Elbab, “Adaptive PI-Based Fuzzy Logic Auto-Tuning Controller Design and Implementation for Tactile Shape Display Device,” 2019 6th International Conference on Advanced Control Circuits and Systems (ACCS) & 2019 5th International Conference on New Paradigms in Electronics & information Technology (PEIT), pp. 32-37, 2019.

M. Saifizi et al., “Adaptive PD Controller Performance for Direct Cooling of Thermoelectric Refrigerator,” in IOP Conference Series: Materials Science and Engineering, vol. 932, no. 1, p. 012063, 2020, doi: 10.1088/1757-899X/932/1/012063.

X. Wu, J. T. Wu, and D. Li, “Designation and Simulation of Environment Laboratory Temperature Control System Based on Adaptive Fuzzy PID,” 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), pp. 583-587, 2018.

N. Aliman, R. Ramli, S. Mohamed Haris, M. Soleimani Amiri, and M. Van, “A robust adaptive-fuzzy-proportional-derivative controller for a rehabilitation lower limb exoskeleton,” Engineering Science and Technology, an International Journal, vol. 35, Nov. 2022, doi: 10.1016/j.jestch.2022.101097.

X. Zhai, Y. Luo, Y. Zhang, and S. Xie, “Fuzzy PD hybrid control of low frequency vibration of annular antenna,” Proc Inst Mech Eng G J Aerosp Eng, vol. 235, no. 6, pp. 718–726, May 2021, doi: 10.1177/0954410020955005.

V. Kumar and A. P. Mittal, “Architecture, performance and stability analysis of a formula-based fuzzy I − fuzzy P − fuzzy D controller,” Soft comput, vol. 15, no. 3, pp. 517–531, Mar. 2011, doi: 10.1007/s00500-009-0536-8.

V. Kumar and A. P. Mittal, “Parallel fuzzy P+fuzzy I+fuzzy D controller: Design and performance evaluation,” International Journal of Automation and Computing, vol. 7, no. 4, pp. 463–471, Nov. 2010, doi: 10.1007/s11633-010-0528-2.

G. Prabhakar, S. Selvaperumal, and P. Nedumal Pugazhenthi, “Fuzzy PD Plus I Control-based Adaptive Cruise Control System in Simulation and Real-time Environment,” IETE J. Res., vol. 65, no. 1, pp. 69–79, Jan. 2019, doi: 10.1080/03772063.2017.1407269.

R. Shakya, K. Rajanwal, S. Patel, and S. Dinkar, “Design and Simulation of PD, PID and Fuzzy Logic Controller for Industrial Application,” International Journal of Information and Computation Technology, vol. 4, no. 4, pp. 363-368, 2014.

H. Li, B. Song, T. Chen, Y. Xie, and X. Zhou, “Adaptive fuzzy PI controller for permanent magnet synchronous motor drive based on predictive functional control,” J. Franklin Inst., vol. 358, no. 15, pp. 7333–7364, Oct. 2021, doi: 10.1016/j.jfranklin.2021.07.024.

G. Shengji, “An Excitation Control Strategy of Synchronous Generator Based on Fuzzy PID,” in 2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) (pp. 397-400, 2021.

M. U. Jan, A. Xin, M. A. Abdelbaky, H. U. Rehman, and S. Iqbal, “Adaptive and Fuzzy PI Controllers Design for Frequency Regulation of Isolated Microgrid Integrated with Electric Vehicles,” IEEE Access, vol. 8, pp. 87621–87632, 2020, doi: 10.1109/ACCESS.2020.2993178.

D. Drajat, S. Sumardi, E. W. Sinuraya, and R. J. Pamungkas, “Design of Temperature Control System for Infant Incubator using Auto Tuning Fuzzy-PI Controller Fuzzy-PI Controller,” International Journal of Engineering and Information Systems (IJEAIS), vol. 3, no. 1, pp. 1-7, 2019.

H. Mittal, L. Mathew, and A. Gupta, “Design and Development of an Infant Incubator for Controlling Multiple Parameters,” Int. J. Emerg. Trends Electr. Electron, vol. 11, no. 5, pp. 2320-9569 2015.

S. B. Utomo, J. F. Irawan, A. Mujibtamala, M. I. Nari, and R. Amalia, “Automatic baby incubator system with fuzzy-PID controller,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1034, no. 1, p. 012023, Feb. 2021, doi: 10.1088/1757-899x/1034/1/012023.

D. Tunjung, P. Prajitno, and D. Handoko, “Temperature and water level control system in water thermal mixing process using adaptive fuzzy PID controller,” in Journal of Physics: Conference Series, vol. 1816, no. 1, p. 012032, 2021, doi: 10.1088/1742-6596/1816/1/012032.

M. Mizanur Rahman and M. Saiful Islam, “Design of a Fuzzy Based Pid Algorithm for Temperature Control of An Incubator,” in Journal of Physics: Conference Series, vol. 1969, no. 1, p. 012055, 2021, doi: 10.1088/1742-6596/1969/1/012055.

A. Alimuddin, R. Arafiyah, I. Saraswati, R. Alfanz, P. Hasudungan, and T. Taufik, “Development and performance study of temperature and humidity regulator in baby incubator using fuzzy-pid hybrid controller,” Energies (Basel), vol. 14, no. 20, Oct. 2021, doi: 10.3390/en14206505.




DOI: https://doi.org/10.18196/jrc.v5i3.21510

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Abd Kholiq, Lamidi Lamidi, Farid Amrinsani, Triwiyanto Triwiyanto, Hafizh Aushaf Mahdy, Ragimova Nazila, Vugar Abdullayev

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

 


Journal of Robotics and Control (JRC)

P-ISSN: 2715-5056 || E-ISSN: 2715-5072
Organized by Peneliti Teknologi Teknik Indonesia
Published by Universitas Muhammadiyah Yogyakarta in collaboration with Peneliti Teknologi Teknik Indonesia, Indonesia and the Department of Electrical Engineering
Website: http://journal.umy.ac.id/index.php/jrc
Email: jrcofumy@gmail.com


Kuliah Teknik Elektro Terbaik