Improved Fast Terminal Sliding Mode Control for a Pediatric Gait Exoskeleton System: Theory and Experimental Results
Authors: 
Jyotindra Narayan, Mohamed Abbas, Bhavik M. Patel, Sanchit Jhunjhunwala, Santosha K DwivedyAuthors Info & Claims
Jyotindra Narayan, Mohamed Abbas, Bhavik M. Patel, Sanchit Jhunjhunwala, Santosha K DwivedyAuthors Info & ClaimsArticle No.: 65, Pages 1 - 6
Abstract
The real-time gait tracking control of a pediatric exoskeleton system is challenging due to parametric uncertainties and external disturbances in the coupled dynamic model. This work proposes an improved fast terminal sliding mode control (IFTSMC) for a pediatric gait exoskeleton system in the passive-assist mode. A new variable exponent reaching law is presented to ensure the rapid approaching of the system states on the sliding surface. Thereafter, a fast terminal sliding mode control (FTSMC) is employed to guarantee the system states near the equilibrium in a finite-time. Lyapunov’s theory is presented to validate the rapid convergence of the gait tracking error in the approaching and siding phases. The IFTSMC scheme is implemented on an experimental setup of the lower-limb exoskeleton with a pediatric subject. The performance of the proposed control scheme is found to be effective in passive-assist gait tracking compared to contrast control schemes.
References
[1]
Rafhael M Andrade, Stefano Sapienza, and Paolo Bonato. 2019. Development of a “transparent operation mode” for a lower-limb exoskeleton designed for children with cerebral palsy. In 2019 IEEE 16th international conference on rehabilitation robotics (ICORR). IEEE, 512–517.
[2]
Cristina Bayon, Teresa Martin-Lorenzo, Beatriz Moral-Saiz, Oscar Ramirez, Alvaro Perez-Somarriba, Sergio Lerma-Lara, Ignacio Martinez, and Eduardo Rocon. 2018. A robot-based gait training therapy for pediatric population with cerebral palsy: goal setting, proposal and preliminary clinical implementation. Journal of neuroengineering and rehabilitation 15, 1 (2018), 1–15.
[3]
Chao-Feng Chen, Zhi-Jiang Du, Long He, Jia-Qi Wang, Dong-Mei Wu, and Wei Dong. 2019. Active disturbance rejection with fast terminal sliding mode control for a lower limb exoskeleton in swing phase. IEEE Access 7 (2019), 72343–72357.
[4]
Elena Delgado, Carlos Cumplido, Jaime Ramos, Elena Garces, Gonzalo Puyuelo, Alberto Plaza, Mar Hernandez, Alba Gutierrez, Thomas Taverner, Marie Andre Destarac, 2021. ATLAS2030 pediatric gait exoskeleton: changes on range of motion, strength and spasticity in children with cerebral palsy. A case series study. Frontiers in pediatrics (2021), 1349.
[5]
E Garcia, J Sancho, D Sanz-Merodio, and e M Prieto. 2018. ATLAS 2020: The pediatric gait exoskeleton project. In Human-Centric Robotics: Proceedings of CLAWAR 2017: 20th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines. World Scientific, 29–38.
[6]
Shuaishuai Han, Haoping Wang, Yang Tian, and Nicolai Christov. 2020. Time-delay estimation based computed torque control with robust adaptive RBF neural network compensator for a rehabilitation exoskeleton. ISA transactions 97 (2020), 171–181.
[7]
SK Hasan and Anoop K Dhingra. 2022. Development of a sliding mode controller with chattering suppressor for human lower extremity exoskeleton robot. Results in Control and Optimization 7 (2022), 100123.
[8]
Bhaben Kalita, Jyotindra Narayan, and Santosha Kumar Dwivedy. 2021. Development of active lower limb robotic-based orthosis and exoskeleton devices: a systematic review. International Journal of Social Robotics 13 (2021), 775–793.
[9]
Zhongjian Kang, Hongguo Yu, and Changchao Li. 2020. Variable-parameter double-power reaching law sliding mode control method. Automatika 61, 3 (2020), 345–351.
[10]
M Khamar and M Edrisi. 2018. Designing a backstepping sliding mode controller for an assistant human knee exoskeleton based on nonlinear disturbance observer. Mechatronics 54 (2018), 121–132.
[11]
Juan C Kupferman, Dimitrios I Zafeiriou, Marc B Lande, Fenella J Kirkham, and Steven G Pavlakis. 2017. Stroke and hypertension in children and adolescents. Journal of child neurology 32, 4 (2017), 408–417.
[12]
Jyotindra Narayan, Mohamed Abbas, and Santosha K Dwivedy. 2023. Robust adaptive backstepping control for a lower-limb exoskeleton system with model uncertainties and external disturbances. Automatika 64, 1 (2023), 145–161.
[13]
Jyotindra Narayan, Aditi A Bhoir, Arunjyoti Borgohain, and Santosha K Dwivedy. 2021. Design and analysis of a stand-aided lower-limb exoskeleton system for pediatric rehabilitation. In 2021 International Conference on Computational Performance Evaluation (ComPE). IEEE, 950–955.
[14]
Jyotindra Narayan and Santosha K Dwivedy. 2021. Robust LQR-based neural-fuzzy tracking control for a lower limb exoskeleton system with parametric uncertainties and external disturbances. Applied Bionics and Biomechanics 2021 (2021).
[15]
Jyotindra Narayan and Santosha K Dwivedy. 2022. Biomechanical study and prediction of lower extremity joint movements using bayesian regularization-based backpropagation neural network. Journal of Computing and Information Science in Engineering 22, 1 (2022).
[16]
Greg Orekhov, Ying Fang, Chance F Cuddeback, and Zachary F Lerner. 2021. Usability and performance validation of an ultra-lightweight and versatile untethered robotic ankle exoskeleton. Journal of neuroengineering and rehabilitation 18, 1 (2021), 1–16.
[17]
Mansour Torabi, Mojtaba Sharifi, and Gholamreza Vossoughi. 2018. Robust adaptive sliding mode admittance control of exoskeleton rehabilitation robots. Scientia Iranica 25, 5 (2018), 2628–2642.
[18]
Jie Wang, Jiahao Liu, Gaowei Zhang, and Shijie Guo. 2022. Periodic event-triggered sliding mode control for lower limb exoskeleton based on human–robot cooperation. ISA transactions 123 (2022), 87–97.
[19]
Siyang Yang, Jiang Han, Lian Xia, and Ye-Hwa Chen. 2020. An optimal fuzzy-theoretic setting of adaptive robust control design for a lower limb exoskeleton robot system. Mechanical Systems and Signal Processing 141 (2020), 106706.
[20]
Shuanghe Yu, Xinghuo Yu, Bijan Shirinzadeh, and Zhihong Man. 2005. Continuous finite-time control for robotic manipulators with terminal sliding mode. Automatica 41, 11 (2005), 1957–1964.
[21]
Xinghuo Yu, Yong Feng, and Zhihong Man. 2020. Terminal sliding mode control–an overview. IEEE Open Journal of the Industrial Electronics Society 2 (2020), 36–52.
[22]
Ting Zhang, Minh Tran, and He Huang. 2018. Design and experimental verification of hip exoskeleton with balance capacities for walking assistance. IEEE/ASME Transactions on mechatronics 23, 1 (2018), 274–285.
[23]
Man Zhihong and Xing Huo Yu. 1997. Terminal sliding mode control of MIMO linear systems. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 44, 11 (1997), 1065–1070.
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- Improved Fast Terminal Sliding Mode Control for a Pediatric Gait Exoskeleton System: Theory and Experimental Results
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July 2023
583 pages
ISBN:9781450399807
DOI:10.1145/3610419
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Published: 02 November 2023
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AIR 2023
AIR 2023: Advances In Robotics - 6th International Conference of The Robotics Society
July 5 - 8, 2023
Ropar, India
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