Fixed-Time Synergetic Control Based Arctic Puffin Optimization for Knee-Exoskeleton Systems
DOI:
https://doi.org/10.12928/biste.v8i4.17182Keywords:
Exoskeleton System, Knee Rehabilitation, Fixed-Time Control, Synergetic Control, Arctic Puffin OptimizationAbstract
Knee exoskeletons are proving to be highly effective tools for people with leg impairments, using external mechanical support to help their knees move more easily. However, to achieve an accurate trajectory tracking, nonlinearities and torque interaction due human–robot interaction can significantly affect the dynamic performance of the system. In this study, a fixed-time synergetic control (FTSC) strategy is proposed for the motion control of the knee-joint of an exoskeleton robot system. Furthermore, the performance of the proposed FTSC scheme is optimized using the Arctic Puffin Optimization (APO). A comparative study between the FTSC and conventional synergetic control (CSC) is carried out under step and sinusoidal motion-tracking scenarios. The results demonstrate the superior tracking performance of the proposed FTSC compared with the conventional CSC. The Integral Time of Absolute Error (IAE) performance index is selected as a quantitative measurement for improvements. The numerical data of the results reveal that the tracking error of the system controlled by the FTSC is reduced by 37.34% and 79.1% compared to that of the system controlled by the CSC for the unit step and sinusoidal signal inputs respectively. Furthermore, the FTSC demonstrated a substantial enhancement when a parameter variation was augmented in the simulation for the sinusoidal signal inputs.
References
M. S. Fragala, E. L. Cadore, S. Dorgo, M. Izquierdo, W. J. Kraemer, M. D. Peterson, and E. D. Ryan, "Resistance training for older adults: position statement from the national strength and conditioning association," The Journal of Strength & Conditioning Research, vol. 33, no. 8, pp. 2019-2052, 2019, https://doi.org/10.1519/JSC.0000000000003230.
L. Fan, L. Yan, and J. Xiao, "Study on the Fuzzy Control Algorithm for Knee Exoskeleton Based on Co-simulation," In International Conference on Mechatronics and Intelligent Robotics, pp. 1123-1129, 2018, https://doi.org/10.1007/978-3-030-00214-5_137.
M. Cristea, G. G. Noja, P. Stefea, and A. L. Sala, "The impact of population aging and public health support on EU labor markets," International journal of environmental research and public health, vol. 17, no. 4, p.1439, 2020, https://doi.org/10.3390/ijerph17041439.
M. Tieland, I. Trouwborst, and B. C. Clark, "Skeletal muscle performance and ageing," Journal of cachexia, sarcopenia and muscle, vol. 9, no. 1, pp.3-19, 2018, https://doi.org/10.1002/jcsm.12238.
G. Li, X. Liang, H. Lu, T. Su, and Z.G. Hou, "Development and Validation of a Self-Aligning Knee Exoskeleton with Hip Rotation Capability," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 32, pp. 472-481, 2024, https://doi.org/10.1109/TNSRE.2024.3354806.
H. S. Majeed, S. K. Kadhim, and A. A. Jaber, "Design of a sliding mode controller for a prosthetic human hand’s finger," Engineering and Technology Journal, vol. 40, no.1, pp.257-266, 2022, https://doi.org/10.30684/etj.v40i1.1943.
J. H. Kim, M. Shim, D. H. Ahn, B. J. Son, S. Y. Kim, D. Y. Kim, Y. S. Baek, and B. K. Cho, "Design of a knee exoskeleton using foot pressure and knee torque sensors," International Journal of Advanced Robotic Systems, vol. 12, no. 8, p.112, 2015, https://doi.org/10.5772/60782.
A. M. Khomami, and F. Najafi, "A survey on soft lower limb cable-driven wearable robots without rigid links and joints," Robotics and Autonomous Systems, vol. 144, p.103846, 2021, https://doi.org/10.1016/j.robot.2021.103846.
Y. Sun, Y. Tang, J. Zheng, D. Dong, X. Chen, and L. Bai, L., "From sensing to control of lower limb exoskeleton: A systematic review," Annual Reviews in Control, vol. 53, pp.83-96, 2022, https://doi.org/10.1016/j.arcontrol.2022.04.003.
N. Touati, I. Saidi, and H. B. H. Mbarek, "PID control of a lower limb rehabilitation exoskeleton," Przegląd Elektrotechniczny, vol. 2024, no. 6, pp. 290-293, 2024, https://doi.org/10.15199/48.2024.06.60.
A. Chevalier, C.M. Ionescu, and R. De Keyser, "Analysis of robustness to gain variation in a fractional-order PI controller for knee joint motion" In ICFDA'14 International Conference on Fractional Differentiation and Its Applications, pp. 1-6, 2014, https://doi.org/10.1109/ICFDA.2014.6967359.
Z. Li, W. Ma, Z. Yin, and H. Guo, "Tracking control of time-varying knee exoskeleton disturbed by interaction torque," ISA transactions, vol. 71, pp.458-466, 2017, https://doi.org/10.1016/j.isatra.2017.08.004.
N. M. Konyak, D. Acharya, and D. K. Das, "Development of Optimal Fuzzy-PID Controller for an Assistant Human Knee Exoskeleton System," In TENCON IEEE Region 10 Conference (TENCON), pp. 777-782, 2023, https://doi.org/10.1109/TENCON58879.2023.10322520.
Z. A. Waheed, and A. J. Humaidi, "Whale Optimization Algorithm Enhances the Performance of Knee-Exoskeleton System Controlled by SMC," Iraqi journal of computers, communications, control and systems engineering, vol. 23, no. 2, pp.125-135, 2023, https://doi.org/10.33103/uot.ijccce.23.2.10.
S. Jenhani, H. Gritli, and J. Narayan, "Robust Position Control of a Knee-Joint Rehabilitation Exoskeleton Using a Linear Matrix Inequalities-Based Design Approach," Applied Sciences, vol. 15, no. 1, p.404, 2025, https://doi.org/10.3390/app15010404.
H. Al-Khazraji, A. K. Ahmend, A.I. Abdulkareem, and A.J. Humaidi, "Terminal synergetic control based cheetah optimizer for knee-exoskeleton systems," Serbian Journal of Electrical Engineering, vol. 22, no. 3, pp.437-452, 2025, https://doi.org/10.2298/SJEE240924006A.
K. Al-Badri, H. Dulaimi, H. Al-Khazraji, and A.J. Humaidi, "Adaptive Neural Network Control for Load-Varying Two-Link Robots Using Honey Badger Optimization," Journal of Robotics and Control (JRC), vol. 6, no. 2, pp.1061-1068, 2025, https://doi.org/10.18196/jrc.v6i2.26370.
S. El Aamery, R. El Bachtiri, and R. El Idrissi, "A Novel Hybrid Artificial Neural Network and Finite-Time Sliding Mode Control Strategy for MPPT in PV Water Pumping Systems with Real-Time Implementation," Arabian Journal for Science and Engineering, vol. 51, pp.1-23, 2025, https://doi.org/10.1007/s13369-025-10901-8.
B. Godspower, D. E. A. Mansour, A. Nada, and T. F. Megahed, "Robust Super-Twisting Control of Active Magnetic Bearing," In 2024 25th International Middle East Power System Conference (MEPCON), pp. 1-6, 2024, https://doi.org/10.1109/MEPCON63025.2024.10850321.
Z. Jin, X. Sun, G. Lei, Y. Guo, and J. Zhu, "Sliding mode direct torque control of SPMSMs based on a hybrid wolf optimization algorithm," IEEE Transactions on Industrial Electronics, vol. 69, no. 5, pp.4534-4544, 2021, https://doi.org/10.1109/TIE.2021.3080220.
A. Naderolasli, "Constrained super-twisting sliding-mode controller for beam and ball nonlinear system stabilization with limited field-of-view constraints," Iranian Journal of Science and Technology, Transactions of Electrical Engineering, vol. 49, no. 4, pp.1645-1659, 2025, https://doi.org/10.1007/s40998-025-00841-2.
J. Qian, K. Li, H. Wu, J. Yang, and X. Li, Synergetic Control of GridConnected Photovoltaic Systems," International Journal of Photoenergy, vol. 2017, no. 1, p.5051489, 2017, https://doi.org/10.1155/2017/5051489.
N. Chiem, "Cascade Control for Trajectory-Tracking Mobile Robots Based on Synergetic Control Theory and Lyapunov Functions," Control Systems and Optimization Letters, vol. 3, no. 1, 14-19, 2025, https://doi.org/10.59247/csol.v3i1.169.
B. Deffaf, H. Farid, H. Benbouhenni, S. Medjmadj, and N. Debdouche, "Synergetic control for three-level voltage source inverter-based shunt active power filter to improve power quality," Energy Reports, vol. 10, pp.1013-1027, 2023, https://doi.org/10.1016/j.egyr.2023.07.051.
F.R. Al-Ani, O.F. Lutfy, and H. Al-Khazraji, "Optimal synergetic and feedback linearization controllers design for magnetic levitation systems: a comparative study," Journal of Robotics and Control (JRC), vol. 6, no. 1, pp.22-30, 2025, https://doi.org/10.18196/jrc.v6i1.24452.
A. K. Abbas, and S. K. Kadhim, "Eliminating Chattering in Prosthetic Fingers Using Classic Synergetic Control," Journal Europeen des Systemes Automatises, vol. 58, no. 1, p.75, 2025, https://doi.org/10.18280/jesa.580109.
S. Huang, L. Xiong, J. Wang, P. Li, Z. Wang, and M. Ma, "Fixed-time synergetic controller for stabilization of hydraulic turbine regulating system," Renewable energy, vol. 157, pp.1233-1242, 2020, https://doi.org/10.1016/j.renene.2020.05.071.
L. Zhang, Y. Wang, Y. Hou, and H. Li, "Fixed-time sliding mode control for uncertain robot manipulators," IEEE Access, vol. 7, pp.149750-149763, 2019, https://doi.org/10.1109/ACCESS.2019.2946866.
A. Polyakov, "Nonlinear feedback design for fixed-time stabilization of linear control systems," IEEE transactions on Automatic Control, vol. 57, no. 8, pp.2106-2110, 2011, https://doi.org/10.1109/TAC.2011.2179869.
S. Sengupta, S. Basak, and A. Peters, “Particle swarm optimization: A survey of historical and recent developments with hybridization perspectives,” Machine Learning and Knowledge Extraction, vol. 1, no. 1, pp. 157–191, 2018, https://doi.org/10.3390/make1010010.
S. Jabber, S. Hashem, and S. Jafer, "Analytical and Comparative Study for Optimization Problems," Iraqi Journal of Computers, Communications, Control and Systems Engineering, vol. 23, no. 4, 46-57, 2023, https://doi.org/10.33103/uot.ijccce.23.4.5.
K. Reddy and K. Saha, “A review of swarm-based metaheuristic optimization techniques and their application to doubly fed induction generator,” Heliyon, vol. 8, no. 10, p. e10956, 2022, https://doi.org/10.1016/j.heliyon.2022.e10956.
S. Tahcfulloh, D. Maulianawati, and D. Wiharyanto, “Optimizing 2.4GHz Wireless Networks in Shrimp Ponds with Particle Swarm Optimization,” Jurnal Ilmiah Teknik Elektro Komputer dan Informatika, vol. 10, no. 4, pp. 817–832, 2024, https://doi.org/10.26555/jiteki.v10i4.30236.
A. K. Ahmed, L. K. Majeed, S. Al-Wais, and H. Al-Khazraji, “Sliding mode position tracking control-based waterwheel plant algorithm for elbow rehabilitation systems," International Journal of Robotics and Control Systems, vol. 6, no. 2, pp.1164-1180, 2026, https://doi.org/10.31763/ijrcs.v6i2.2708.
S. W. Shneen, J. M. D. Alkhasraji, and M. Q. Sulttan, “Internet-based Control of Thermo-optical Plant Improvement based on the PID-GWO System,” Journal Fuzzy System Control, vol. 2, no. 3, pp. 197–202, 2024, https://doi.org/10.59247/jfsc.v2i3.257.
H. Al-Rammahi and A. Y. Asaad, “A particle swarm optimization-enhanced support vector regression model for accurate prediction of concrete compressive strength using slump test data,” Control Systems and Optimization Letters, vol. 3, no. 3, pp. 272–279, 2025, https://doi.org/10.59247/csol.v3i3.224.
M. A. Al-Ali, O. F. Lutfy and H. Al-Khazraj, "Investigation of optimal controllers on dynamics performance of nonlinear active suspension systems with actuator saturation," Journal of Robotics and Control (JRC), vol. 5, no. 4, pp.1041-1049, 2024, https://doi.org/10.18196/jrc.v5i4.22139.
M. J. Mohamed, and L. T. Rasheed, "Design of nonlinear PID and FOPID controllers for electronic throttle valve plate’s position," Journal of Electrical and Computer Engineering, vol. 2024, no. 1, p.9984750, 2024, https://doi.org/10.1155/2024/9984750.
P. Chotikunnan, W. Khotakham, A. Wongkamhang, A. Nirapai, P. Imura, K. Roongpraser, R. Chotikunnan, and N. Thongpance, N. "Genetic Algorithm-Optimized LQR for Enhanced Stability in Self-Balancing Wheelchair Systems," Control Systems and Optimization Letters, vol. 2, no. 3, 327-335, 2024, https://doi.org/10.59247/csol.v2i3.161.
V. C. Bui, V. Q. Le, A. N. Ngo, and C. H. Canh, “Firefly Algorithm-Based PID Optimization for Active Suspension Systems in Electric Vehicles,” Journal of Fuzzy Systems and Control, vol. 3, no. 2, pp. 142–148, 2025, https://doi.org/10.59247/jfsc.v3i2.311.
M. N. Ajaweed, A. H. Issa, and M. T. Muhssin, “Design and implementation of an OFOPID controller for Iraqi two areas power system using ant-colony optimization algorithm,” Iraqi Journal of Computers, Communications, Control and Systems Engineering, vol. 26, no. 1, pp. 83–100, 2026, https://doi.org/10.33103/2617-3352.1519.
H. Al-Khazraji, C. Cole, W. and Guo, "Multi-objective particle swarm optimisation approach for production-inventory control systems," Journal of Modelling in Management, vol. 13, no. 4, pp.1037-1056, 2018, https://doi.org/10.1108/JM2-02-2018-0027.
W.C. Wang, W.C. Tian, D.M. Xu, and H.F. Zang, "Arctic puffin optimization: A bio-inspired metaheuristic algorithm for solving engineering design optimization," Advances in Engineering Software, vol. 195, p.103694, 2024, https://doi.org/10.1016/j.advengsoft.2024.103694.
G. Gauri, M. Kashish, G. Shruti, S.A. Iqbal, and J. More, "Load Frequency Control of Multi-Area Power System Using Arctic Puffin Optimization," In 2025 IEEE 1st International Conference on Smart and Sustainable Developments in Electrical Engineering (SSDEE), pp. 01-05, 2025, https://doi.org/10.1109/SSDEE64538.2025.10968053.
R. Firmansyah, P. D. Widayaka, M. R. Fahrezy, P. P. S. Saputra, and D. Septian, "Voltage Control of DC Microgrid using Arctic Puffin Optimization Algorithm for Tuning of Sliding Mode Control Gain," In 2024 Seventh International Conference on Vocational Education and Electrical Engineering (ICVEE), pp. 279-282, 2024, https://doi.org/10.1109/ICVEE63912.2024.10823965.
A. K. Abdelaal, A. M. Shaheen, A. A. El-Fergany, and M. H. Alqahtani, "Sliding mode control based dynamic voltage restorer for voltage sag compensation," Results in Engineering, vol. 24, p.102936, 2024, https://doi.org/10.1016/j.rineng.2024.102936.
A. Alkamachi, "Robust Speed Control of Permanent Magnet DC Motors Using an Arctic Puffin Optimized PI Controller and Nonlinear Disturbance Observer," Buletin Ilmiah Sarjana Teknik Elektro, vol. 8, no. 3, pp.684-698, 2026, https://doi.org/10.12928/biste.v8i3.15723.
M. A. E. Mohamed, K. Jagatheesan, and B. Anand, “Modern PID/FOPID controllers for frequency regulation of interconnected power system by considering different cost functions,” Scientific Reports, vol. 13, no. 1, p. 14084, 2023, https://doi.org/10.1038/s41598-023-41024-5.
S. Singh, V. P. Singh, A. Mathur, T. K. Bashishtha, S. Padmanaban, and T. Varshney, “Airport microgrid control using integral-of-absolute-error having high renewable penetration,” Scientific Reports, vol. 15, no. 1, p. 23550, 2025, https://doi.org/10.1038/s41598-025-04820-9.
L. Majeed, S. Al-Wais, M. Mustafaa, H. Al-Khazraji, and R. Kadhim, "Cheetah-Optimizer-Based Nonlinear Controller for Single-Link Flexible-Joint Manipulators: A Comparative Simulation Study," International Journal of Robotics and Control Systems, vol. 6, no. 3, 2107-2122, 2026, https://doi.org/10.31763/ijrcs.v6i3.2576.
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