Hostname: page-component-55f67697df-sqlfs Total loading time: 0 Render date: 2025-05-08T15:12:25.174Z Has data issue: false hasContentIssue false
  • English
  • Français

Optimisation of synchronisation control parameters for enhanced bilateral teleoperation system

Published online by Cambridge University Press:  08 October 2024

Naveen Kumar ,
Niharika Thakur Open the ORCID record for Niharika Thakur [Opens in a new window]  and
Yogita Gupta
Naveen Kumar
Affiliation:
Department of Electronics and Communication Engineering, Manav Rachna University, Faridabad, Haryana, India
Niharika Thakur*
Affiliation:
Department of Electronics and Communication Engineering, Manav Rachna University, Faridabad, Haryana, India
Yogita Gupta
Affiliation:
Department of Electronics and Communication Engineering, Manav Rachna University, Faridabad, Haryana, India
*
Corresponding author: Niharika Thakur; Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Bilateral teleoperation systems encounter challenges in achieving synchronisation between master and slave robots due to communication time delays. This paper addresses the instability caused by these delays and proposes a solution through advanced control algorithms. Nonlinear optimisation algorithms might only sometimes deliver solutions in the allotted time, particularly when handling complicated, high-dimensional issues or when optimisation iterations are extensive. The study first develops a comprehensive mathematical model encompassing the dynamics and communication intricacies of both master and slave sides in teleoperation. By recognising the limitations of existing proportional-derivative controllers in compensating for communication errors, a sequential quadratic programming-proportional-integral-derivative (SQP-PID) controller is introduced. This controller accumulates and rectifies synchronisation delay errors, ensuring precise control without steady-state deviations. The proposed SQP-PID controller stands out for its ability to handle steady-state errors effectively, offering swift response and maintaining stability. Leveraging the SQP optimisation algorithm, it intelligently tunes the parameters, minimising synchronisation errors. The approach capitalises on the simplicity, performance, and robustness of the SQP-PID controller, providing a promising avenue for enhancing bilateral teleoperation systems’ accuracy and stability, maintaining initial discrepancy with a best fitness value of 0.98 % in varied operating conditions.

Keywords

bilateral teleoperation systemssequential quadratic programming (SQP)PID controllerssynchronisation errors
Type
Research Article
Information
Robotica , Volume 42 , Issue 11 , November 2024 , pp. 3639 - 3656
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Kumar, N., Thakur, N. and Gupta, Y., “Time delay compensated disturbance observer-based sliding mode slave controller and neural network model for bilateral teleoperation system,” Intell Serv Robot 17, 1–13 (2024).CrossRefGoogle Scholar
Elek, R. N. and Haidegger, T., “Robot-assisted minimally invasive surgical skill assessment—Manual and automated platforms,” Acta Polytech Hung 16(8), 141–169 (2019).Google Scholar
Beaman, C. B., Kaneko, N., Meyers, P. M. and Tateshima, S., “A review of robotic interventional neuroradiology,” Am J Neuroradiol 42(5), 808–814 (2021).CrossRefGoogle ScholarPubMed
N. Hameedha and A. Mohideen, Network Delay Mitigated Remote Robot Control with Force Feedback for Improved QoS (2022).Google Scholar
Wang, F., Qian, Z., Lin, Y. and Zhang, W., “Design and rapid construction of a cost-effective virtual haptic device,” IEEE/ASME Trans Mechatr 26(1), 66–77 (2020).Google Scholar
Lunghi, G., Marin, R., Di Castro, M., Masi, A. and Sanz, P. J., “Multimodal human-robot interface for accessible remote robotic interventions in hazardous environments,” IEEE Access 7, 127290–127319 (2019).CrossRefGoogle Scholar
Yan, Y., Liu, Y., Fang, J., Lu, Y. and Jiang, X., “Application status and development trends for intelligent perception of distribution network,” High Volt 6(6), 938–954 (2021).CrossRefGoogle Scholar
Bolarinwa, J.O., Enhancing Tele-Operation-Investigating the Effect of Sensory Feedback On Performance (Faculty of Engineering and Technology, University of the West of England, Bristol, 2022). Doctoral dissertationGoogle Scholar
Kumar, N., Thakur, N. and Khanna, Y., “Time delay Independent of Bilateral Tele-Robotic System using Wave Variable Approach,” In: 2022 8th International Conference on Signal Processing and Communication (ICSC), (2022) pp. 669–674.Google Scholar
Thakur, N., Awasthi, Y. K., Hooda, M. and Siddiqui, A. S., “Adaptive whale optimization for intelligent multi-constraints power quality improvement under deregulated environment,” J Eng Des Technol 17(3), 490–514 (2019).Google Scholar
Mariano-Hernández, D., Hernández-Callejo, L., Zorita-Lamadrid, A., Duque-Pérez, O. and García, F. S., “A review of strategies for building energy management system: Model predictive control, demand side management, optimization, and fault detect & diagnosis,” J Build Eng 33, 101692 (2021).CrossRefGoogle Scholar
Kaleybar, H. J., Davoodi, M., Brenna, M. and Zaninelli, D., “Applications of genetic algorithm and its variants in rail vehicle systems: A bibliometric analysis and comprehensive review,” IEEE Access 11, 68972–68993 (2023).CrossRefGoogle Scholar
Nasr, M., Islam, M. M., Shehata, S., Karray, F. and Quintana, Y., “Smart healthcare in the age of AI: Recent advances, challenges, and future prospects,” IEEE Access 9, 145248–145270 (2021).CrossRefGoogle Scholar
Alahakoon, S., Roy, R. B. and Arachchillage, S. J., “Optimizing load frequency control in standalone marine microgrids using meta-heuristic techniques,” Energies 16(13), 4846 (2023).CrossRefGoogle Scholar
Lyu, H., Kong, D., Pang, G., Wang, B., Yu, Z., Pang, Z. and Yang, G., “GuLiM: A hybrid motion mapping technique for teleoperation of medical assistive robot in combating the COVID-19 pandemic,” IEEE Trans Med Robot Bio 4(1), 106–117 (2022).CrossRefGoogle Scholar
Su, Y., Lloyd, L., Chen, X. and Chase, J. G., “Latency mitigation using applied HMMs for mixed reality-enhanced intuitive teleoperation in intelligent robotic welding,” Int J Adv Manuf Technol 126(5-6), 2233–2248 (2023).CrossRefGoogle Scholar
Shokri-Ghaleh, H., Alfi, A., Ebadollahi, S., Shahri, A. M. and Ranjbaran, S., “Unequal limit cuckoo optimization algorithm applied for optimal design of nonlinear field calibration problem of a triaxial accelerometer,” Measurement 164, 107963 (2020).CrossRefGoogle Scholar
Rehman, W. U., Wang, X., Hameed, Z. and Gul, M. Y., “Motion synchronization control for a large civil aircraft’s hybrid actuation system using fuzzy logic-based control, techniques,” Mathematics 11(7), 1576 (2023).CrossRefGoogle Scholar
Mohammadi, L. and Alfi, A., “Guaranteed cost control in delayed teleoperation systems under actuator saturation,” Iran J Sci Technol Trans Electr Eng 43(4), 827–835 (2019).Google Scholar
Ishiguro, Y., Makabe, T., Nagamatsu, Y., Kojio, Y., Kojima, K., Sugai, F. and Inaba, M., “Bilateral humanoid teleoperation system using whole-body exoskeleton cockpit TABLIS,” IEEE Robot Autom Lett 5(4), 6419–6426 (2020).CrossRefGoogle Scholar
Naseer, F., Khan, M. N. and Altalbe, A., “Intelligent time delay control of telepresence robots using novel deep reinforcement learning algorithm to interact with patients,” Appl Sci 13(4), 2462 (2023).CrossRefGoogle Scholar
Ouyang, P. R., Dam, T., Huang, J. and Zhang, W. J., “Contour tracking control in position domain,” Mechatronics 22(7), 934–944 (2012).CrossRefGoogle Scholar
Shokri-Ghaleh, H. and Alfi, A., “A comparison between optimization algorithms applied to synchronization of bilateral teleoperation systems against time delay and modeling uncertainties,” Appl Soft Comput 24, 447–456 (2014).CrossRefGoogle Scholar