Hybrid Multi-Servo Motor Controller Within an IoT-Enabled Smart Mechatronics Framework

Authors

  • Dodit Suprianto
  • Ginanjar Adi
  • Rini Agustina
  • Nurul Hidayati
  • Azam Imammuddin

DOI:

https://doi.org/10.25139/inform.v10i2.10100

Keywords:

Hybrid Control, Multi-Servo Motor, IoT, MQTT, Potentiometer-Based Control, Real-Time Performance

Abstract

The increasing demand for precise motor control in industrial automation and IoT-integrated applications has driven the development of hybrid control systems for multi-servo motor management. Existing solutions often rely solely on either IoT-based automation or standalone manual control, limiting adaptability in environments with unreliable network connectivity. This study proposes a hybrid control system that integrates local potentiometer-based control with IoT-enabled remote operation to enhance flexibility and reliability. An experimental approach is employed to design and evaluate the hybrid control system, utilizing a modular controller board and MQTT as an IoT communication protocol. The system’s performance is assessed based on response time and synchronization accuracy under varying network conditions. Experimental findings demonstrate that the proposed system effectively balances remote accessibility while ensuring on-site reliability. The integration of MQTT QoS level 2 enhances real-time performance by ensuring the accurate delivery of messages. Measured delays range from 21.72 ms to 55.61 ms, with jitter values between 1.17 ms and 33.89 ms, highlighting the impact of data traffic on control precision. By addressing latency, synchronization, and connectivity challenges, the proposed system bridges the gap between IoT-driven automation and manual control mechanisms, providing a scalable and reliable solution for broader automation applications.

References

M. Ryalat, E. Franco, H. Elmoaqet, N. Almtireen, and G. Al-Refai, “The integration of advanced mechatronic systems into industry 4.0 for smart manufacturing,” Sustain., vol. 16, no. 19, pp. 1–39, 2024, doi: 10.3390/su16198504.

H. Chen, “The practice of mechatronics technology in intelligent manufacturing,” in Proc.SPIE, Mar. 2024, vol. 12981, p. 1298141. doi: 10.1117/12.3014884.

A. Pchelintsev and N. Malev, “INTELLIGENT control in mechatronic systems,” Ekon. I Upr. Probl. RESHENIYA, 2024, doi: 10.36871/ek.up.p.r.2024.07.05.005.

A. Aliyev and A. Yalchinkaya, “Modern prospects for the application of mechatronics and robotics capabilities,” J. Ecohumanism, vol. 3, no. 7, pp. 765–769, 2024, doi: 10.62754/joe.v3i7.4245.

A. Filipescu, I. Stamatescu, G. Simion, D. Ionescu, and A. Filipescu, “IoT-cloud based control of a flexible assembly/disassembly mechatronic system in the framework of industries 4.0 and 5.0,” IEEE Int. Conf. Control Autom. ICCA, no. 47, pp. 534–539, 2024, doi: 10.1109/ICCA62789.2024.10591866.

J. Zhao and B. Huang, “Research on the integration of intelligent technology and mechatronics in mechanical manufacturing,” Front. Sci. Eng., vol. 2, no. 9, pp. 29–32, 2022, doi: 10.54691/fse.v2i9.2230.

J. Huanca, J. Zamora, J. Cornejo, and R. Palomares, “Mechatronic design and kinematic analysis of 8 dof serial robot manipulator to perform electrostatic spray painting process on electrical panels,” Proc. 2022 IEEE Eng. Int. Res. Conf. EIRCON 2022, pp. 1–4, 2022, doi: 10.1109/EIRCON56026.2022.9934104.

M. Ntuen, O. Osanaiye, I. Adeosun, I. B. Muhammad, I. Lawrence, and B. M. Sambo, “Using mechatronics to facilitate manufacturing processes,” 2023 2nd Int. Conf. Multidiscip. Eng. Appl. Sci. ICMEAS 2023, vol. 1, pp. 1–3, 2023, doi: 10.1109/ICMEAS58693.2023.10379366.

J. Cornejo et al., “Industrial, collaborative and mobile robotics in latin america: review of mechatronic technologies for advanced automation,” Emerg. Sci. J., vol. 7, no. 4, pp. 1430–1458, 2023, doi: 10.28991/ESJ-2023-07-04-025.

W. Ding, J. Li, and J. Yuan, “An improved model predictive torque control for switched reluctance motors with candidate voltage vectors optimization,” IEEE Trans. Ind. Electron., vol. 70, no. 5, pp. 4595–4607, 2022, doi: 10.1109/TIE.2022.3190895.

S. Lee, C. Hwang, J. Shim, and J. I. Ha, “A control method of servo motor drives for fast dynamic response and low torque ripple,” 2022 IEEE Energy Convers. Congr. Expo. ECCE 2022, pp. 1–5, 2022, doi: 10.1109/ECCE50734.2022.9947638.

A. O. Deab, K. Karthikumar, M. Karuppiah, and P. A. G. Sankar, “A new optimal space vector modulation with dtc switching strategy for induction motor control,” Int. J. Appl. Power Eng., vol. 13, no. 4, pp. 862–873, 2024, doi: 10.11591/ijape.v13.i4.pp862-873.

T. T. Nguyen, T. H. Nguyen, and J. W. Jeon, “Explicit model predictive speed control for permanent magnet synchronous motor with torque ripple minimization,” IEEE Access, vol. 11, no. October, pp. 134199–134210, 2023, doi: 10.1109/ACCESS.2023.3335992.

X. Sun, Y. Zhu, Y. Cai, M. Yao, Y. Sun, and G. Lei, “Optimized-sector-based model predictive torque control with sliding mode controller for switched reluctance motor,” IEEE Trans. Energy Convers., vol. 39, no. 1, pp. 379–388, 2024, doi: 10.1109/TEC.2023.3301000.

M. Ghibeche, K. Kouzi, D. Difi, and A. Ouanouki, “Investigation of predictive direct torque control of double star permanent magnet synchronous machine (dspmsm),” Stud. Eng. Exact Sci., vol. 5, no. 1, pp. 2672–2684, 2024, doi: 10.54021/seesv5n1-132.

H. Lin et al., “Three-stage duty cycle-based deadbeat predictive torque control for three-phase spmsms with cmv reduction,” IEEE Trans. Power Electron., vol. 38, no. 9, pp. 11385–11398, 2023, doi: 10.1109/TPEL.2023.3288184.

C. Hui, H. Yanjie, P. Yinbin, and Z. Tao, “A method for reducing torque ripple of switched reluctance motor based on partitioned tsf,” Front. Energy Res., vol. 12, no. May, pp. 1–11, 2024, doi: 10.3389/fenrg.2024.1381950.

J. Zhou, M. Cheng, H. Wen, X. Yan, M. Tong, and W. Wang, “Modeling and suppression of torque ripple in pmsm based on the general airgap field modulation theory,” IEEE Trans. Power Electron., vol. 37, no. 10, pp. 12502–12512, 2022, doi: 10.1109/TPEL.2022.3174395.

V. Q. B. Ngo, N. Kim Anh, and N. Khanh Quang, “FPGA-based adaptive pid controller using mlp neural network for tracking motion systems,” IEEE Access, vol. 12, no. May, pp. 91568–91574, 2024, doi: 10.1109/ACCESS.2024.3422015.

Y. F. Li, Z. W. Xu, Y. J. Zhang, Y. Bin Wu, and L. Chuang, “On the design of simultaneous motion controller for the four-axis scara system,” Proc. Int. Conf. Power Electron. Drive Syst., vol. 2023-Augus, no. August, pp. 1–6, 2023, doi: 10.1109/PEDS57185.2023.10246556.

S. Goyal, A. Shankar, K. C. Das, A. Singh, S. Oli, and M. M. Sati, “Manual and adaptive tuned pid controllers for industrial application,” 2024 4th Int. Conf. Adv. Comput. Innov. Technol. Eng. ICACITE 2024, pp. 1953–1958, 2024, doi: 10.1109/ICACITE60783.2024.10616874.

A. K. Maurya, M. Dutt Dwivedi, and H. Khan, “Implementation of pid controller tuning method for load frequency control in multi area power system,” 4th Int. Conf. Innov. Pract. Technol. Manag. 2024, ICIPTM 2024, no. Iciptm, pp. 1–6, 2024, doi: 10.1109/ICIPTM59628.2024.10563927.

C. Lertyosbordin, D. Wongsanont, N. Khurukitwanit, and W. Saowapark, “A framework for remote robot actuation using ros integrated with mqtt,” 2024 Int. Tech. Conf. Circuits/Systems, Comput. Commun. ITC-CSCC 2024, pp. 1–4, 2024, doi: 10.1109/ITC-CSCC62988.2024.10628235.

S. Opacin, L. Rizvanovic, B. Leander, S. Mubeen, and A. Caudevic, “Developing and evaluating mqtt connectivity for an industrial controller,” 12th Mediterr. Conf. Embed. Comput. MECO 2023, pp. 6–10, 2023, doi: 10.1109/MECO58584.2023.10154921.

J. Xin et al., “Design and implementation of an efficient hardware coprocessor ip core for multi-axis servo control based on universal soc,” Electron., vol. 12, no. 2, 2023, doi: 10.3390/electronics12020452.

M. Cristian Marin, M. Cerutti, S. Batista, and M. Brambilla, “A multi-protocol iot platform for enhanced interoperability and standardization in smart home,” Proc. - IEEE Consum. Commun. Netw. Conf. CCNC, pp. 1–6, 2024, doi: 10.1109/CCNC51664.2024.10454663.

H. Yu, “Method for remote-control of electrical automation instruments over wireless networks based on plc technology,” IEEE 1st Int. Conf. Ambient Intell. Knowl. Informatics Ind. Electron. AIKIIE 2023, pp. 1–6, 2023, doi: 10.1109/AIKIIE60097.2023.10390481.

A. H. Embong, L. Asbollah, and S. B. A. Hamid, “JOURNAL of mechanical engineering and sciences empowering industrial automation labs with iot: a case study on real-time monitoring and control of induction motors using siemens plc and node-red,” vol. 18, no. 2, pp. 10004–10016, 2024.

H. Zhang, I. Automation, P. Optimization, and S. Analysis, “Design and implementation of industrial automation control system based on plc,” J. Electron. Inf. Sci., vol. 9, no. 2, pp. 120–126, 2024, doi: 10.23977/jeis.2024.090215.

I. Ghinea and G. Bucur, “Advanced automatic system for remote control in the oil and gas industry,” Rom. J. Pet. Gas Technol., vol. 4 (75), no. 2, pp. 181–192, 2023, doi: 10.51865/jpgt.2023.02.18.

N. H. Damia Mohamad Razam and S. Sara Rais, “IoT-enabled automatic plant watering system,” 8th Int. Conf. Recent Adv. Innov. Eng. Empower. Comput. Anal. Eng. Through Digit. Innov. ICRAIE 2023, vol. 2023, pp. 1–6, 2023, doi: 10.1109/ICRAIE59459.2023.10468389.

K. Singh, A. Jain, and P. Thiyagarajan, “Design and implementation of integrated control system for iot enabled home automation,” Proc. - 2022 4th Int. Conf. Adv. Comput. Commun. Control Networking, ICAC3N 2022, pp. 1433–1437, 2022, doi: 10.1109/ICAC3N56670.2022.10074496.

D. M. Murali and R. L. Rao, “Cost efficient five way home automation with feedback system,” Interantional J. Sci. Res. Eng. Manag., vol. 07, no. 03, pp. 1–4, 2023, doi: 10.55041/ijsrem18075.

X. Li, “Design of equipment automation control and remote supervision system based on artificial intelligence algorithm,” in 2023 Int. Conf. Power, Electr. Eng. Electron. Control, 2023, pp. 515–520. doi: 10.1109/PEEEC60561.2023.00106.

R. Doshi, “Distributed mqtt broker : a load-balanced redis-based architecture,” 2024 Int. Conf. Emerg. Smart Comput. Informatics, pp. 1–6, 2024, doi: 10.1109/ESCI59607.2024.10497427.

S. R. Hashim, R. A. Enad, A. M. Al-Khafagi, and N. K. Abdalhameed, “The facilities of detection by using a tool of wireshark,” Indones. J. Electr. Eng. Comput. Sci., vol. 31, no. 1, pp. 329–336, 2023, doi: 10.11591/ijeecs.v31.i1.pp329-336.

Downloads

Published

2025-07-04

How to Cite

Suprianto, D., Adi, G., Agustina, R., Hidayati, N., & Imammuddin, A. (2025). Hybrid Multi-Servo Motor Controller Within an IoT-Enabled Smart Mechatronics Framework. Inform : Jurnal Ilmiah Bidang Teknologi Informasi Dan Komunikasi, 10(2), 121–128. https://doi.org/10.25139/inform.v10i2.10100

Issue

Section

Articles

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.