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Manipulability based model predictive control of rehabilitation robot | ||
| Journal of Mathematical Modeling | ||
| دوره 14، شماره 1، خرداد 2026، صفحه 305-313 اصل مقاله (515.22 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22124/jmm.2025.30154.2695 | ||
| نویسندگان | ||
| Ali Pourmomtaz؛ Behnam Miripour Fard* ؛ Hamed Kouhi | ||
| Faculty of Mechanical Engineering, University of Guilan, Rasht, Iran | ||
| چکیده | ||
| One challenge with rehabilitation exoskeletons is the potential for reaching singular configurations, reducing efficiency. Additionally, paths generated for an exoskeleton may not always exhibit optimal manipulability and dexterity, unlike healthy humans who perform tasks with maximum manipulability. This paper considers a multi-degree-of-freedom model for the exoskeleton robot, deriving its kinematic and dynamic equations. The robot's kinematic manipulability is formulated based on the Jacobian, and Model Predictive Control (MPC) is employed for control. The novelty lies in incorporating the cost function related to the robot's kinematic manipulability alongside other cost functions within the MPC framework. Dynamic simulations evaluate this approach, showing that the manipulability criterion conflicts with tracking error. This research demonstrates that using the manipulability index as a constraint or part of the cost function in MPC can help prevent the robot from reaching singular points and enhance manipulability and dexterity in hand rehabilitation. | ||
| کلیدواژه‌ها | ||
| Rehabilitation robot؛ model predictive control؛ manipulability | ||
| مراجع | ||
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[1] S.Y. Raza, S.F. Ahmed, A. Ali, K.A. Kadir, M.K. Joyo, S. Khan, Z. Janin, Model predictive control for upper limb rehabilitation robotic system under noisy condition, Proc. IEEE 5th Int. Conf. Smart Instrumentation, Measurement and Application (ICSIMA), Nov. 2018, 1–4. [2] M.A. Destarac, J.G. Montano M. Cardona, E. Gomez, Orte exoskeleton: Kinematic analysis and dynamic modeling, Proc. IEEE 38th Central America and Panama Convention (CONCAPAN XXXVIII), 2018. [3] H.S. Lo, S.Q. Xie, Exoskeleton robots for upper-limb rehabilitation: State of the art and future prospects, Med. Eng. Phys. 34 (2012) 261–268. [4] S.M.T. Zarandi, S.K.H. Sani, M.R.A. Tootoonchi, A.A. Tootoonchi, M.G Farajzadeh, Design and implementation of a real-time nonlinear model predictive controller for a lower limb exoskeleton with input saturation, Iran. J. Sci. Technol. Trans. Electr. Eng. 45 (2021) 309–320. [5] A. Ali, S.F. Ahmed, M.K. Joyo, K. Kushsairy, MPC-PID comparison for controlling therapeutic upper limb rehabilitation robot under perturbed conditions, Proc. IEEE 3rd Int. Conf. Eng. Technol. Soc. Sci. (ICETSS), 2017. [6] Y. Yan, et al., Trajectory tracking control of wearable upper limb rehabilitation robot based on Laguerre model predictive control, Robot. Auton. Syst. 179 (2024) 104745. [7] G.B. Avanzini, A.M. Zanchettin, P. Rocco, Constrained model predictive control for mobile robotic manipulators, Robotica 36 (2018) 19–38. [8] G. Chiriatti, A. Bottiglione, G. Palmieri, Manipulability optimization of a rehabilitative collaborative robotic system, Machines 10 (2022) 452. [9] M.C. Molet, J.L. Prat, Analysis of arm movements during activities of daily living for the design of an active upper limb exoskeleton for adults with Duchenne, M.Sc. Thesis, Dept. Mech. Eng., Universidad Politecnica de Catalunya, Barcelona, Spain, 2016. [10] D.A. Winter, Biomechanics and Motor Control of Human Movement, 3rd ed., John Wiley & Sons, Hoboken, NJ, USA, 2009. | ||
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