OPTIMAL SLIDING MODE CONTROLLER DESIGN BASED ON WHALE OPTIMIZATION ALGORITHM FOR LOWER LIMB REHABILITATION ROBOT
Noor SABAH
noors@uowasit.edu.iqUniversity of Wasit, Electrical Engineering Department (Iraq)
Ekhlas HAMEED
Mustansiriyah University, Computer Engineering Department (Iraq)
Muayed S AL-HUSEINY
University of Wasit, Electrical Engineering Department (Iraq)
Abstract
The Sliding Mode Controllers (SMCs) are considered among the most common stabilizer and controllers used with robotic systems due to their robust nonlinear scheme designed to control nonlinear systems. SMCs are insensitive to external disturbance and system parameters variations. Although the SMC is an adaptive and model-based controller, some of its values need to be determined precisely. In this paper, an Optimal Sliding Mode Controller (OSMC) is suggested based on Whale Optimization Algorithm (WOA) to control a two-link lower limb rehabilitation robot. This controller has two parts, the equivalent part, and the supervisory controller part. The stability assurance of the controlled rehabilitation robot is analyzed based on Lyapunov stability. The WO algorithm is used to determine optimal parameters for the suggested SMC. Simulation results of two tested trajectories (linear step signal and nonlinear sine signal) demonstrate the effectiveness of the suggested OSMC with fast response, very small overshoot, and minimum steady-state error.
Keywords:
Optimal Sliding Mode Controller, Whale Optimization Algorithm, lower limb, rehabilitation robotReferences
Abbasimoshaei, A., & Mohammadimoghaddam, M. (2020). Design for a New Hand Rehabilitation (Vol. 1). Springer. https://doi.org/10.1007/978-3-030-58147-3
DOI: https://doi.org/10.1007/978-3-030-58147-3
Google Scholar
Almaghout, K., Tarvirdizadeh, B., Alipour, K., & Hadi, A. (2020). Design and control of a lower limb rehabilitation robot considering undesirable torques of the patient’s limb. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 234(12), 1457–1471. https://doi.org/10.1177/0954411920947849
DOI: https://doi.org/10.1177/0954411920947849
Google Scholar
Alshatti, A. (2019). Design and Control of Lower Limb Assistive Exoskeleton for Hemiplegia Mobility (Doctoral dissertation). University of Sheffield.
Google Scholar
Babaiasl, M., Goldar, S. N., Barhaghtalab, M. H., & Meigoli, V. (2015). Sliding mode control of an exoskeleton robot for use in upper-limb rehabilitation. International Conference on Robotics and Mechatronics, ICROM 2015, 694–701. https://doi.org/10.1109/ICRoM.2015.7367867
DOI: https://doi.org/10.1109/ICRoM.2015.7367867
Google Scholar
DeCarlo, R. A., Zak, S. H., & Matthews, G. P. (1988). Variable structure control of nonlinear multivariable systems: a tutorial. Proceedings of the IEEE, 76(3), 212–232, https://doi.org/10.1109/5.4400
DOI: https://doi.org/10.1109/5.4400
Google Scholar
Furlan, A. D., Irvin, E., Munhall, C., Giraldo-Prieto, M., Master, R. M., Danak, S., Costante, A., Pitzul, K. B., Bhide, R. P., Marchenko, S., Mahood, Q., David, J. A., Flannery, J. F., & Bayley, M. (2021). Rehabilitation service models for people with physical and/or mental disability living in low- and middle-income countries: A systematic review. Journal of Rehabilitation Medicine, 50(6), 487–498. https://doi.org/10.2340/16501977-2325
DOI: https://doi.org/10.2340/16501977-2325
Google Scholar
Hung, J. Y., Gao, W., & Hung, J. C. (1993). Variable Structure Control : A Survey. IEEE Trans. Ind. Electron, 40(1), 2–22.
DOI: https://doi.org/10.1109/41.184817
Google Scholar
Liu, J., Zhang, Y., Wang, J., & Chen, W. (2018). Adaptive sliding mode control for a lower-limb exoskeleton rehabilitation robot. Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018 (pp. 1481–1486). IEEE. https://doi.org/10.1109/ICIEA.2018.8397943
DOI: https://doi.org/10.1109/ICIEA.2018.8397943
Google Scholar
Maalej, B., Medhaffar, H., Chemori, A., & Derbel, N. (2020). A Fuzzy Sliding Mode Controller for Reducing Torques Applied to a Rehabilitation Robot. Proceedings of the 17th International Multi-Conference on Systems, Signals and Devices, SSD 2020 (pp. 740–746). https://doi.org/10.1109/SSD49366.2020.9364130
DOI: https://doi.org/10.1109/SSD49366.2020.9364130
Google Scholar
Mirjalili, S., & Lewis, A. (2016). The Whale Optimization Algorithm. Advances in Engineering Software, 95, 51–67. https://doi.org/10.1016/j.advengsoft.2016.01.008
DOI: https://doi.org/10.1016/j.advengsoft.2016.01.008
Google Scholar
Mohammed, H. M., Umar, S. U., & Rashid, T. A. (2019). A Systematic and Meta-Analysis Survey of Whale Optimization Algorithm. Computational Intelligence and Neuroscience, 2019, 8718571. https://doi.org/10.1155/2019/8718571
DOI: https://doi.org/10.1155/2019/8718571
Google Scholar
Nguyen, T. V. M., Ha, Q. P., & Nguyen, H. T. (1989). A Chattering-Free Variable Structure Controller for Tracking of Robotic Manipulators. Retrivied from https://www.araa.asn.au/acra/acra2003/papers/02.pdf
Google Scholar
Rezage, G. Al, & Tokhi, M. O. (2016). Fuzzy PID control of lower limb exoskeleton for elderly mobility. 2016 20th IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2016 – Proceedings (pp. 1–6). IEEE. https://doi.org/10.1109/AQTR.2016.7501310
DOI: https://doi.org/10.1109/AQTR.2016.7501310
Google Scholar
Rodrigues, A., & Rodrigues, A. (2018). Prise en charge des traumatisés médullaires. Le Praticien En Anesthesie Reanimation, 8–11. https://doi.org/10.1016/j.pratan.2018.08.010
DOI: https://doi.org/10.1016/j.pratan.2018.08.010
Google Scholar
Rupal, B. S., Rafique, S., Singla, A., & Singla, E. (2017). Lower-limb exoskeletons : Research trends and regulatory guidelines in medical and non-medical applications. International Journal of Advanced Robotic Systems, November-December, 1–27. https://doi.org/10.1177/1729881417743554
DOI: https://doi.org/10.1177/1729881417743554
Google Scholar
Saryanto, W. Y., & Cahyadi, A. I. (2016). Modeling and Design of Low Cost Lower Limb Rehabilitation Robot Control System for Post - Stroke Patient using PWM Controller. International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS, 16(1), 101–108.
Google Scholar
Winter, D. A. (2009). Biomechanics And Motor Control Of Human Movement (Fourth Ed.). John Wiley & Sons, Inc. Yang, T., & Gao, X. (2020). Adaptive Neural Sliding-Mode Controller for Alternative Control Strategies in Lower Limb Rehabilitation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(1), 238–247. https://doi.org/10.1109/TNSRE.2019.2946407
DOI: https://doi.org/10.1109/TNSRE.2019.2946407
Google Scholar
Zhou, J., Zhou, Z., & Ai, Q. (2016). Impedance Control of the Rehabilitation Robot Based on Sliding Mode Control. Mechanical Engineering and Control Systems, 135–140. https://doi.org/10.1142/9789814740616_0030
DOI: https://doi.org/10.1142/9789814740616_0030
Google Scholar
Authors
Ekhlas HAMEEDMustansiriyah University, Computer Engineering Department Iraq
Authors
Muayed S AL-HUSEINYUniversity of Wasit, Electrical Engineering Department Iraq
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