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Page 354                      Zhang et al. Intell. Robot. 2025, 5(2), 333-54  I http://dx.doi.org/10.20517/ir.2025.17


                  2014 Second RSI/ISM International Conference on Robotics and Mechatronics (ICRoM), Tehran, Iran. Oct 15-17, 2014. IEEE, 2014; pp.
                  588-94. DOI
               24. Tang, S.; Chen, L.; Barsotti, M.; et al. Kinematic synergy of multi-DoF movement in upper limb and its application for rehabilitation
                  exoskeleton motion planning. Front. Neurorobot. 2019, 13, 99. DOI
               25. Shahbazi, H.; Parandeh, R.; Jamshidi, K. Implementation of imitation learning using natural learner central pattern generator neural
                  networks. Neural Netw. 2016, 83, 94–108. DOI
               26. Lauretti, C.; Cordella, F.; Ciancio, A. L.; et al. Learning by demonstration for motion planning of upper-limb exoskeletons.  Front.
                  Neurorobot. 2018, 12, 5. DOI
               27. Nguiadem, C.; Raison, M.; Achiche, S. Motion planning of upper-limb exoskeleton robots: a review. Appl. Sci. 2020, 10, 7626. DOI
               28. Wu, Q.; Wang, X.; Chen, B.; Wu, H. Development of a minimal-intervention-based admittance control strategy for upper extremity
                  rehabilitation exoskeleton. IEEE Trans. Syst. Man. Cybern. Syst. 2018, 48, 1005-16. DOI
               29. Li, X.; Yang, Q.; Song, R. Performance-based hybrid control of a cable-driven upper-limb rehabilitation robot. IEEE Trans. Biomed. Eng.
                  2021, 68, 1351-9. DOI
               30. Zhang, M.; Wang, C.; Zhang, C.; Li, P.; Liu, L. A unified switching control framework for continuous robot-assisted training. IEEE/ASME
                  Trans. Mechatron. 2024, 29, 2743-55. DOI
               31. Wu, J.; Huang, J.; Wang, Y.; Xing, K.; Xu, Q. Fuzzy PID control of a wearable rehabilitation robotic hand driven by pneumatic muscles.
                  In: 2009 International Symposium on Micro-NanoMechatronics and Human Science, Nagoya, Japan. Nov 09-11, 2009. IEEE, 2009; pp.
                  408-13. DOI
               32. Proietti, T.; Jarrassé, N.; Roby-Brami, A.; Morel, G. Adaptive control of a robotic exoskeleton for neurorehabilitation. In: 2015 7th
                  International IEEE/EMBS Conference on Neural Engineering (NER), Montpellier, France. Apr 22-24, 2015. IEEE, 2015; pp. 803-6. DOI
               33. Koshkouei, A. J.; Zinober, A. S. I. Terminal sliding mode control of MIMO linear systems. In: Proceedings of the 2002 American
                  Control Conference (IEEE Cat. No.CH37301), Anchorage, USA. May 08-10, 2022. IEEE, 2002; pp. 2106-11. DOI
               34. Feng, Y.; Yu, X.; Han, F. On nonsingular terminal sliding-mode control of nonlinear systems. Automatica. 2013, 49, 1715-22. DOI
               35. Zou, A. M.; Kumar, K. D.; Hou, Z. G.; Liu, X. Finite-time attitude tracking control for spacecraft using terminal sliding mode and
                  Chebyshev neural network. IEEE Trans. Syst. Man. Cyber. B. 2011, 41, 950-63. DOI
               36. Kim, K. S.; Park, Y.; Oh, S. H. Designing robust sliding hyperplanes for parametric uncertain systems: a Riccati approach. Automatica
                  2000, 36, 1041-8. DOI
               37. Choi, H. H. LMI-based sliding surface design for integral sliding mode control of mismatched uncertain systems. IEEE Trans. Autom.
                  Control. 2007, 52, 736-42. DOI
               38. Wen, C. C.; Cheng, C. C. Design of sliding surface for mismatched uncertain systems to achieve asymptotical stability. J. Frankl. Inst.
                  2008, 345, 926-41. DOI
               39. Utkin, V.; Shi, J. Integral sliding mode in systems operating under uncertainty conditions. In: Proceedings of 35th IEEE Conference on
                  Decision and Control, Kobe, Japan. Dec 13, 1996. IEEE, 1996; pp. 4591-6. DOI
               40. Wei, X.; Zhang, H.; Guo, L. Composite disturbance-observer-based control and terminal sliding mode control for uncertain structural
                  systems. Int. J. Syst. Sci. 2009, 40, 1009–17. DOI
               41. Man, Z.; Xing, H. Y. Terminal sliding mode control of MIMO linear systemst. IEEE Trans. Circuits. Syst. I. Fundam. Theory. Appl. 1997,
                  44, 1065-70. DOI
               42. Wang, C.; Zhang, Y.; Peng, L; Zou, A. M.; Hou, Z. G. Dynamic modelling and adaptive control of an upper-limb robotic exoskeleton. In:
                  2024 IEEE International Conference on Advanced Information, Mechanical Engineering, Robotics and Automation (AIMERA), Wulumuqi,
                  China. May 18-19, 2024. IEEE, 2024; pp. 249-54. DOI
               43. Hogan, N. An organizing principle for a class of voluntary movements. J. Neurosci. 1984, 4, 2745-54. DOI
               44. Yang, X. R; Lin, X.; Yang, Y.; Zou, A. M. Finite-time attitude tracking control of rigid spacecraft with multiple constraints. IEEE Trans.
                  Aerosp. Electron. Syst. 2024, 60, 3688-97. DOI
               45. Kang, H. B.; Wang, J. H. Adaptive control of 5 DOF upper-limb exoskeleton robot with improved safety. ISA Trans. 2013, 52, 844-52.
                  DOI
               46. Yu, S.; Yu, X.; Shirinzadeh, B.; Man, Z. Continuous finite-time control for robotic manipulators with terminal sliding mode. Automatica.
                  2005, 41, 1957–64. DOI
               47. Feng, Y.; Yu, Y. H.; Han, F. L. On nonsingular terminal sliding-mode control of nonlinear systems. Automatica. 2013, 49, 1715-22. DOI
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