Robust nonlinear control of the hydroïd humanoid robotic arm: a comparative study of sliding mode strategies for high-precision trajectory tracking

Youssef Mahmoud, Mohamed Elasswad, Ahmed Abdellatif, Maya Sleiman, Khaled Khalil, Samer Alfayad

Abstract


This paper presents the modelling, control and performance evaluation of a redundant 7-DOF anthropomorphic robotic arm of HYDROÏD humanoid hydraulic robot. A kinematic framework based on the Denavit–Hartenberg (D–H) convention is developed and integrated with a biomimetic design that embeds physiological motion constraints. To bridge theory and implementation, the system is modelled in a CAD-to-Simscape Multibody environment, capturing nonlinear actuator dynamics, torque saturation, and joint coupling. A comparative analysis is conducted between linear and robust nonlinear control strategies, including State Feedback, LQR, SMC, TSMC, and STSMC. The controllers are evaluated through tracking of complex trajectories—rectangle, infinity, and parallelogram—under disturbance and payload variation scenarios. Results show that sliding mode-based controllers significantly outperform linear approaches, reducing RMSE from over 20° (linear controllers) to below 10° (SMC variants). STSMC achieves the highest steady-state accuracy with MAE as low as 0.44°, while TSMC provides superior robustness with maximum deviation limited to approximately 0.83°. These findings confirm the effectiveness of advanced sliding mode strategies for high-DOF humanoid robotic systems operating under realistic conditions.

 

Received: 26 April 2026

Accepted: 13 May 2026

Published: 17 June 2026


Keywords


Humanoid Robotics; Sliding Mode Control; Robust Nonlinear Control; Trajectory Tracking; Disturbance Rejection

Full Text:

PDF

References


M. B. El-Den and A. Hebala, “Challenges in closing the gap between software and hardware in robotics,” Robotics : Integration, Manufacturing and Control, vol. 1, no. 1, p. 11, Jun. 2024, doi: https://doi.org/10.21622/rimc.2024.01.1.922.

H. Fawzy, A. Elbrawy, M. Amr, O. Eltanekhy, E. Khatab, and O. Shalash, “A systematic review: computer vision algorithms in drone surveillance,” Robotics : Integration, Manufacturing and Control, vol. 2, no. 1, pp. 1–10, 2025, doi: https://doi.org/10.21622/RIMC.2025.02.1.1149.

Y. Tong, H. Liu, and Z. Zhang, “Advancements in Humanoid Robots: A Comprehensive Review and Future Prospects,” IEEE/CAA Journal of Automatica Sinica, vol. 11, no. 2, pp. 301–328, Feb. 2024, doi: https://doi.org/10.1109/jas.2023.124140.

S. Sun, H. Huang, and C. Li, “Advancements in humanoid robot dynamics and learning-based locomotion control methods,” Intelligence & Robotics, vol. 5, no. 3, pp. 631–60, Jul. 2025, doi: https://doi.org/10.20517/ir.2025.32.

A. A. Azhari, W. M. Ahmed, M. F. El-Khatib, and A. Abdellatif, “AI-Driven Trajectory Planning of Dentatron: A Compact 4-DOF Dental Robotic Manipulator,” Biomimetics, vol. 10, no. 12, p. 803, Dec. 2025, doi: https://doi.org/10.3390/biomimetics10120803.

P. Ferrari et al., “Multi-contact planning and control for humanoid robots: Design and validation of a complete framework,” Robotics and Autonomous Systems, vol. 166, pp. 104448–104448, May 2023, doi: https://doi.org/10.1016/j.robot.2023.104448.

S. Samadi, J. Roux, A. Tanguy, S. Caron, and A. Kheddar, “Humanoid Control Under Interchangeable Fixed and Sliding Unilateral Contacts,” IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 4032–4039, Apr. 2021, doi: https://doi.org/10.1109/lra.2021.3066965.

M. Herrmann, T. Hempel, and A. Al-Hamadi, “A Real-Time Digital Twin Framework for the TIAGo Service Robot,” 2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 6065–6068, Oct. 2025, doi: https://doi.org/10.1109/smc58881.2025.11343553.

J. Wang, Y. Jiang, Y. Li, H. Zhang, and Y. Wang, “A Novel Neural-Network-Based MPC Framework for Whole-Body Motion Optimization and Control of Redundant Humanoid Robots,” IEEE Transactions on Automation Science and Engineering, vol. 23, pp. 7920–7931, 2026, doi: https://doi.org/10.1109/tase.2026.3679503.

F. Ficuciello, L. Villani, and B. Siciliano, “Variable Impedance Control of Redundant Manipulators for Intuitive Human–Robot Physical Interaction,” IEEE Transactions on Robotics, vol. 31, no. 4, pp. 850–863, Aug. 2015, doi: https://doi.org/10.1109/tro.2015.2430053.

A. Ajoudani, A. M. Zanchettin, S. Ivaldi, A. Albu-Schäffer, K. Kosuge, and O. Khatib, “Progress and prospects of the human–robot collaboration,” Autonomous Robots, vol. 42, no. 5, pp. 957–975, Oct. 2017, doi: https://doi.org/10.1007/s10514-017-9677-2.

C. Xu, M. Huang, Z. Liu, and T. Lan, “Collision Detection for Robotic Manipulators using LSTM Autoencoder,” 2025 6th International Conference on Control, Robotics and Intelligent System (CCRIS), pp. 1–5, Aug. 2025, doi: https://doi.org/10.1109/ccris65764.2025.11192873.

W. Jie, Z. Yudong, B. Yulong, H. H. Kim, and M. C. Lee, “Trajectory Tracking Control Using Fractional-Order Terminal Sliding Mode Control With Sliding Perturbation Observer for a 7-DOF Robot Manipulator,” IEEE/ASME Transactions on Mechatronics, vol. 25, no. 4, pp. 1886–1893, Aug. 2020, doi: https://doi.org/10.1109/tmech.2020.2992676.

Sushilkumar Ambhore, “A Comprehensive Study on Robot Learning from Demonstration,” in 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), Bangalore, India, Mar. 2020, pp. 291–299. doi: https://doi.org/10.1109/icimia48430.2020.9074946.

Z. Xu, X. Yang, and M. Hu, “Nonsingular Terminal Sliding-Mode Control For Robotic Manipulator System With Adaptive Uncertainty and Disturbance Rejection,” 2023 China Automation Congress (CAC), pp. 7208–7213, Nov. 2023, doi: https://doi.org/10.1109/cac59555.2023.10450478.

S. Ahmed, H. Wang, and Y. Tian, “Adaptive High-Order Terminal Sliding Mode Control Based on Time Delay Estimation for the Robotic Manipulators With Backlash Hysteresis,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 2, pp. 1128–1137, Feb. 2021, doi: https://doi.org/10.1109/tsmc.2019.2895588.

P. A. Hosseinabadi, A. Soltani, H. Schwartz, H. Pota, and S. Mekhilef, “Fixed‐time sliding mode observer‐based controller for a class of uncertain nonlinear double integrator systems,” Asian Journal of Control, vol. 25, no. 5, pp. 3456–3473, Mar. 2023, doi: https://doi.org/10.1002/asjc.3052.

A. Abdellatif, M. E. Asswad, M. Sleiman, K. Khalil, and S. Alfayad, “Composite Hydraulic Integration: A New Step Toward Lightweight Hydraulic Robots,” Malaysian Journal on Composites Science and Manufacturing, vol. 16, no. 1, pp. 150–166, Apr. 2025, doi: https://doi.org/10.37934/mjcsm.16.1.150166.

E. Amrollah, A. Abdellatif, S. Alfayad, and F. B. Ouezdou, “Performance enhancement of an integrated electro-hydraulic actuator using dynamic modeling and optimization,” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 237, no. 12, pp. 2815–2832, Dec. 2022, doi: https://doi.org/10.1177/09544062221142404.

E. A. M., A. A., A. S., and K. K., “Novel Lightweight Hydraulic Integration Methodology for Robotic Applications,” Journal of Advanced Research in Applied Sciences and Engineering Technology, vol. 49, no. 2, pp. 102–117, Aug. 2024, doi: https://doi.org/10.37934/araset.49.2.102117.




DOI: https://dx.doi.org/10.21622/RIMC.2026.03.1.2013

Refbacks

  • There are currently no refbacks.


Copyright (c) 2026 Youssef Mahmoud, Mohamed El Asswad, Ahmed Abdellatif, Maya Sleiman, Khaled Khalil, Samer Alfayad


Robotics : Integration, Manufacturing and Control

E-ISSN: 3009-7967

P-ISSN: 3009-6987

 

Published by:

Academy Publishing Center (APC)

Arab Academy for Science, Technology and Maritime Transport (AASTMT)

Alexandria, Egypt

rimc@aast.edu