Simplified Sliding Mode Control of a Single-Link Planar Robot
Article Sidebar
Main Article Content
Abstract
Robotic technologies are becoming more advanced and are becoming more popular. Requirements are high levels of accuracy and operational speed, such as in surgery and manufacturing. These targets were highly challenging and could be enhanced by employing suitable control systems. Nonlinear control schemes were characterised by high accuracy and robustness, but by high computational time. Hence, the study simplified the Sliding Mode Control (SMC) scheme for a single link planar robot and was referred to as the Simplified Sliding Mode Control (RSMC), which was compared with the normal version referred to as Normal Sliding Mode Control (NSMC) and the gain scheduling based Proportional Derivative Control (GPDC). The effect considered was friction, and it was limited to simulation studies conducted using the SIMULINK/MATLAB software. Results showed that the proposed controller, RSMC, has an algorithm length that is at least 50% shorter than that of the NSMC, with a simplicity similar to that of the GPDC. Results also indicated achieving a settling time of 1.5s, a rise time of 0.8s, 0% overshoot, and a cumulative error of about 250, maintaining the same results with disturbance. The system with the NSMC showed the corresponding parameters as 2.0s, 1.8s, 0% and 260, respectively, without disturbance, and as 3s, 3s, 0% and 310, respectively, with disturbance. It therefore implied that a shorter RSMC algorithm means lower execution time. The RSMC showed superior performance, indicating higher accuracy, operational speed and robustness.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Emerging Technologies and Engineering Journal is licensed under a Creative Commons Attribution License 4.0 (CC BY-4.0).
References
A. R. Lanfranco, A. E. Castellanos, J. P. Desai, and W. C. Meyers, "Robotic Surgery: A Current Perspective," Annals of Surgery, vol. 239, no. 1, pp. 14 - 21, 2004, doi: https://doi.org/10.1097/01.sla.0000103020.19595.7d.
A. A. Gajjar et al., "Evolution of robotics in spine surgery: A historical perspective," Interdisciplinary Neurosurgery, vol. 33, p. 101721, 2023, doi: https://doi.org/10.1016/j.inat.2023.101721.
A. Goia, V. Gilard, R. Lefaucheur, M.-L. Welter, D. Maltête, and S. Derrey, "Accuracy of the robot-assisted procedure in deep brain stimulation," The International Journal of Medical Robotics and Computer Assisted Surgery, vol. 15, no. 6, p. e2032, 2019, doi: https://doi.org/10.1002/rcs.2032.
L. Furlanetti et al., "Targeting accuracy of robot-assisted deep brain stimulation surgery in childhood-onset dystonia: a single-center prospective cohort analysis of 45 consecutive cases," (in English), Journal of Neurosurgery: Pediatrics, vol. 27, no. 6, pp. 677-687, 01 Jun. 2021 2021, doi: https://doi.org/10.3171/2020.10.PEDS20633.
B. Veejay and B. Dev, "Robotics in neurosurgery," The Annals of The Royal College of Surgeons of England, vol. 100, no. 6, pp. 23-26, 2018, doi: https://doi.org/10.1308/rcsann.supp1.19.
A. Grau, M. Indri, L. L. Bello, and T. Sauter, "Industrial robotics in factory automation: From the early stage to the Internet of Things," in IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, 29 Oct.-1 Nov. 2017 2017, pp. 6159-6164, doi: https://doi.org/10.1109/IECON.2017.8217070.
M. Li, A. Milojević, and H. Handroos, "Robotics in Manufacturing—The Past and the Present," in Technical, Economic and Societal Effects of Manufacturing 4.0: Automation, Adaption and Manufacturing in Finland and Beyond, M. Collan and K.-E. Michelsen Eds. Cham: Springer International Publishing, 2020, pp. 85-95, doi: https://doi.org/10.1007/978-3-030-46103-4_4
A. Hassan, A. A. Al-Ahdal, A. w. A. Saif, and J. U. Yahaya, "Analysis of Robust Control Method for Single Link Flexible Manipulator," in 2024 21st International Multi-Conference on Systems, Signals & Devices (SSD), 22-25 April 2024 2024, pp. 465-473, doi: https://doi.org/10.1109/SSD61670.2024.10548073.
M. Mohamed, F. Anayi, M. Packianather, B. A. Samad, and K. Yahya, "Simulating LQR and PID controllers to stabilise a three-link robotic system," in 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 28-29 April 2022 2022, pp. 2033-2036, doi: https://doi.org/10.1109/ICACITE53722.2022.9823512.
P. Boscariol, A. Gasparetto, and V. Zanotto, "Model Predictive Control of a Flexible Links Mechanism," Journal of Intelligent and Robotic Systems, vol. 58, no. 2, pp. 125-147, 2010, doi: https://doi.org/10.1007/s10846-009-9347-5.
N. M. Tahir, S. M. Hassan, Z. Mohamed, and A. G. Ibrahim, "Output based input shaping for optimal control of single link flexible manipulator," International Journal on Smart Sensing and Intelligent Systems, vol. 10, no. 2, pp. 1-20, 2017, doi: https://doi.org/10.21307/ijssis-2017-216.
G. Then Mozhi, M. Banu Sundareswari, and K. Dhanalakshmi, "Bidirectional Position Control of a Prismatic joint for Motorized Single Link Robotic Arm Using Adaptive Super- Twisting Sliding Mode Control," Journal of The Institution of Engineers (India): Series B, vol. 104, no. 5, pp. 1035-1042, 2023, doi: https://doi.org/10.1007/s40031-023-00908-w.
P. N. Dao, N. T. Dang, T. L. Nguyen, and G. K. Dinh, "Finite-time sliding mode Control strategies for perturbed input-constrained nonlinear bilateral teleoperation systems with variable-time communication delays," Intelligent Service Robotics, vol. 18, no. 2, pp. 363-378, 2025, doi: https://doi.org/10.1007/s11370-025-00590-5.
H. G. Dirara, F. T. Yareshe, and C. M. Abdissa, "Design and Analysis of Adaptive Fuzzy Super-Twisting Sliding Mode Controller for Uncertain 2-DOF Robotic Manipulator," IEEE Access, vol. 13, pp. 110241-110254, 2025, doi: https://doi.org/10.1109/ACCESS.2025.3581449.
J. Ji and P. Jiang, "Research on Predefined Time Sliding Mode Control Method for High-Speed Maglev Train Based on Finite Time Disturbance Observer," Actuators, vol. 14, no. 1, p. 21, 2025, doi: https://doi.org/10.3390/act14010021.
A. H. Mhmood and M. N. Mahyuddin, "H∞ Sliding Mode Control: A Recent Review of Applications and Design Methods," IEEE Access, vol. 13, pp. 136687-136715, 2025, doi: https://doi.org/10.1109/ACCESS.2025.3594707.
N. Cherigui, A. Chemidi, A. Tahour, and M. Horch, "A new advanced third-order sliding mode control with adaptive gain adjustment using fuzzy logic technique for standalone photovoltaic systems," AIMS Electronics and Electrical Engineering, vol. 9, no. 2, pp. 243-259, 2025, doi: https://doi.org/10.3934/electreng.2025012.
H. Sira-RamÍRez, "On the dynamical sliding mode control of nonlinear systems," International Journal of Control, vol. 57, no. 5, pp. 1039-1061, 1993, doi: https://doi.org/10.1080/00207179308934429.
C. L. Phillips, H. T. Nagle, and A. Chakrabortty, Digital control system analysis and design. England: Prentice Hall Press, 2015.
J. Liu and X. Wang, "Advanced Sliding Mode Control," in Advanced Sliding Mode Control for Mechanical Systems: Design, Analysis and MATLAB Simulation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 81-96, doi: https://doi.org/10.1007/978-3-642-20907-9_3