Hostname: page-component-76fb5796d-vfjqv Total loading time: 0 Render date: 2024-04-25T17:13:23.666Z Has data issue: false hasContentIssue false
  • English
  • Français

Continuous Finite-Time Torque Control for Flexible Assistance Exoskeleton with Delay Variation Input

Published online by Cambridge University Press:  13 August 2020

Tao Xue Open the ORCID record for Tao Xue [Opens in a new window] ,
ZiWei Wang ,
Tao Zhang ,
Ou Bai ,
Meng Zhang  and
Bin Han
Tao Xue
Affiliation:
Department of Automation, Tsinghua University, Beijing100084, China
ZiWei Wang
Affiliation:
Department of Automation, Tsinghua University, Beijing100084, China
Tao Zhang*
Affiliation:
Department of Automation, Tsinghua University, Beijing100084, China
Ou Bai
Affiliation:
Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA
Meng Zhang
Affiliation:
Department of Automation, Tsinghua University, Beijing100084, China Move Robotics Technology Company, Ltd., Shanghai201306, China
Bin Han
Affiliation:
School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan430074, China
*
*Corresponding author. E-mail: taozhang@tsinghua.edu.cn
Get access Rights & Permissions [Opens in a new window]

Summary

Accurate torque control is a critical issue in the compliant human–robot interaction scenario, which is, however, challenging due to the ever-changing human intentions, input delay, and various disturbances. Even worse, the performances of existing control strategies are limited on account of the compromise between precision and stability. To this end, this paper presents a novel high-performance torque control scheme without compromise. In this scheme, a new nonlinear disturbance observer incorporated with equivalent control concept is proposed, where the faster convergence and stronger anti-noise capability can be obtained simultaneously. Meanwhile, a continuous fractional power control law is designed with an iteration method to address the matched/unmatched disturbance rejection and global finite-time convergence. Moreover, the finite-time stability proof and prescribed control performance are guaranteed using constructed Lyapunov function with adding power integrator technique. Both the simulation and experiments demonstrate enhanced control accuracy, faster convergence rate, perfect disturbance rejection capability, and stronger robustness of the proposed control scheme. Furthermore, the evaluated assistance effects present improved gait patterns and reduced muscle efforts during walking and upstair activity.

Keywords

Compliant human–robot interactionSeries elastic actuatorForce controlFinite-time controlFluctuated delay inputRobotic exoskeleton
Type
Articles
Information
Robotica , Volume 39 , Issue 2 , February 2021 , pp. 291 - 316
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Xue, T., Wang, Z., Zhang, T. and Zhang, M., “Adaptive oscillator-based robust control for flexible hip assistive exoskeleton,” IEEE Robot. Autom. Lett. 4(4), 3318–3323 (2019).Google Scholar
Meuleman, J., van Asseldonk, E., van Oort, G., Rietman, H. and van der Kooij, H., “LOPES II—Design and evaluation of an admittance controlled gait training robot With shadow-leg approach,” IEEE Trans. Neural Syst. Rehabil. Eng. 24(3), 352–363 (2016).CrossRefGoogle ScholarPubMed
Lee, H. J., Lee, S., Chang, W. H., Seo, K., Shim, Y., Choi, B. O., Ryu, G. H. and Kim, Y. H., “A wearable hip assist robot can improve gait function and cardiopulmonary metabolic efficiency in elderly adults,” IEEE Trans. Neural Syst. Rehabil. Eng. 25(9), 1549–1557 (2017).Google ScholarPubMed
Xue, T., Wang, Z., Zhang, T., Zhang, M. and Li, Z., “The Control System for Flexible Hip Assistive Exoskeleton,” Proceedings of 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO) (2018) pp. 697–702.Google Scholar
Shuanghe, Y., Xinghuo, Y. and Stonier, R. J., “Continuous finite-time control for robotic manipulators with terminal sliding mode,” Automatica 41(11), 1957–1964 (2005).Google Scholar
Wang, Z., Xue, T., Liang, B., and Chen, Z., “Backstepping Based Robust Control for Space Tele-Robot Systems with Finite-Time Convergence,” Proceedings of 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO) (2018) pp. 1419–1424.Google Scholar
Bing, X. and Yin, S., “Velocity-free fault-tolerant and uncertainty attenuation control for a class of nonlinear systems,” IEEE Trans. Ind. Electron. 63(7), 4400–4411 (2016).Google Scholar
Shtessel, Y., Edwards, C., Fridman, L. and Levant, A., Sliding Mode Control and Observation (Springer, New York, 2014).CrossRefGoogle Scholar
Shihua, L., Haibin, S., Yang, J. and Xinghuo, Y., “Continuous finite-time output regulation for disturbed systems under mismatching condition,” IEEE Trans. Autom. Control 60(1), 277–282 (2015).Google Scholar
Shihua, L., Shihong, D. and Qi, L., “Global set stabilisation of the spacecraft attitude using finite-time control technique,” Int. J. Control 82(5), 822–836 (2009).Google Scholar
Meng, W., Lei, S., Yin, W., Shuai, D. and Jingtai, L., “Continuous Finite-Time Control Approach for Series Elastic Actuator,” Proceedings of IEEE Conference on Decision and Control (2016) pp. 843–848.Google Scholar
Pratt, G. and Williamson, M., “Human Robot Interaction and Cooperative Robots,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (1995) pp. 399–406.Google Scholar
Keehong, S., Kyung, K. R. and Young, J. P., “Adaptive Oscillator-Based Control for Active Lower-Limb Exoskeleton and its Metabolic Impact,” Proceedings of IEEE International Conference on Robotics and Automation (2018) pp. 6752–6758.Google Scholar
Lee, Y., Kim, Y. J., Lee, J., Lee, M., Choi, B., Kim, J., Park, Y. J. and Choi, J., “Biomechanical design of a novel flexible exoskeleton for lower extremities,” IEEE/ASME Trans. Mechatron. 22(5), 2058–2069 (2017).Google Scholar
Huo, W., Mohammed, S., Amirat, Y. and Kong, K., “Fast gait mode detection and assistive torque control of an exoskeletal robotic orthosis for walking assistance,” IEEE Trans. Robot. 34(4), 1035–1052 (2018).Google Scholar
Calanca, A. and Paolo, F., “Human-adaptive control of series elastic actuators,” Robotica 32(8), 1301–1316 (2014).CrossRefGoogle Scholar
Calanca, A., Luca, C. and Paolo, F., “Robust force control of series elastic actuators,” Actuators 3(3), 182–204 (2014).Google Scholar
Kyoungchul, K., Joonbum, B. and Masayoshi, T., “Control of rotary series elastic actuator for ideal force-mode actuation in human–robot interaction applications,” IEEE/ASME Trans. Mechatron. 14(1), 105–118 (2009).Google Scholar
Matsuda, M., Mataki, Y., Mutsuzaki, H., Yoshikawa, K., Takahashi, K., Enomoto, K., Sano, K., Mizukami, M., Tomita, K., Ohguro, H. and Iwasaki, N., “Immediate effects of a single session of robot-assisted gait training using Hybrid Assistive Limb (HAL) for cerebral palsy,” J. Phys. Ther. Sci. 30(2), 207–212 (2018).CrossRefGoogle ScholarPubMed
Soekadar, S. R., Matthias, W. and Cristina, G. P., “Hybrid EEG/EOG-based brain/neural hand exoskeleton restores fully independent daily living activities after quadriplegia.” Sci. Robot. 1(1), eaag3296-1 (2016).Google ScholarPubMed
Zheng, E., Manca, S., Yan, T., Parri, A., Vitiello, N. and Wang, Q., “Gait phase estimation based on noncontact capacitive sensing and adaptive oscillators,” IEEE Trans. Biomed. Eng. 64(10), 2419–2430 (2017).CrossRefGoogle ScholarPubMed
Qingcong, W., Xingsong, W., Fengpo, D. and Xiaobo, Z., “Design and control of a powered hip exoskeleton for walking assistance,” Int. J. Adv. Robot. Syst. 12(3), 18 (2015).Google Scholar
Vaughan, C. L., Davis, B. L. and O’connor, J. C., Dynamics of Human Gait (Kiboho Publishers, Cape Town, 1999).Google Scholar
Beckenbach, E. F. and Bellman, R., Inequalities, vol. 30 (Springer Science & Business Media, Berlin, Germany, 2012).Google Scholar
Shihong, D. and Shihua, L., “Second-order sliding mode controller design subject to mismatched term,” Automatica 77, 388–392 (2017).Google Scholar
Manini, T. M., Hong, S. L. and Brian, C. C., “Aging and muscle: A neuron’s perspective,” Curr. Opin. Clin. Nutr. Metab. Care 16(1), 21–26 (2013).CrossRefGoogle ScholarPubMed
Sungho, J., “Hypothetical neural control of human bipedal walking with voluntary modulation,” Med. Biolog. Eng. Comput. 46(2), 179–193 (2008).Google Scholar
Jamaludin, Z., Hendrik, V. B. and Jan, S., “Friction compensation of an feed table using friction-model-based feedforward and an inverse-model-based disturbance observer,” IEEE Trans. Ind. Electron. 56(10), 3848–3853 (2009).CrossRefGoogle Scholar
Wenhua, C., Ballance, D. J. and Gawthrop, P. J., “A nonlinear disturbance observer for robotic manipulators,” IEEE Trans. Ind. Electron. 47(4), 932–938 (2000).Google Scholar
Zhang, T., Tran, M. and Huang, H., “Admittance shaping-based assistive control of SEA-driven robotic hip exoskeleton,” IEEE/ASME Trans. Mechatron. 24(4), 1508–1519 (2019).CrossRefGoogle Scholar
Aguirre-Ollinger, G., Narayan, A., Cheng, H. J. and Yu, H., “Exoskeleton Control for Post-stoke Gait Training of a Paretic Limb Based on Extraction of the Contralateral Gait Phase,” Proceedings of International Symposium on Wearable Robotics (2018) pp. 294–298.Google Scholar
Keehong, S., Jusuk, L., Younbaek, L. and Taesin, H., “Fully Autonomous Hip Exoskeleton Saves Metabolic Cost of Walking.” Proceedings of 2016 IEEE International Conference on Robotics and Automation (2016) pp. 4628–4635.Google Scholar
Ziwei, W., Zhang, C., Yiman, Z. and Xingyao, Y., “Adaptive finitetime control for bilateral teleoperation systems with jittering time delays.” Int. J. Robust Nonlinear Control 29(4), 1007–1030 (2018).Google Scholar
Kammen, K., Boonstra, A. M., Woude, L. H. V., Reinders-Messelink, H. A. and Otter, R., “The combined effects of guidance force, bodyweight support and gait speed on muscle activity during able-bodied walking in the Lokomat,” Clin. Biomechan. 36, 65–73 (2016).CrossRefGoogle ScholarPubMed
Jayaraman, A., O’brien, M. K., Madhavan, S., Mummidisetty, C. K., Roth, H. R., Hohl, K., Tapp, A., Brennan, K., Kocherginsky, M., Williams, K. J., Takahashi, H. and Rymer, W. Z., “Stride management assist exoskeleton vs functional gait training in stroke: A randomized trial,” Neurology 92(3), 263–273 (2019).CrossRefGoogle ScholarPubMed
Oh, S. and Kong, K., “High-precision robust force control of a series elastic actuator,” IEEE/ASME Trans. Mechatron. 22(1), 71–80 (2016).CrossRefGoogle Scholar
Paine, N., Oh, S. and Sentis, L., “Design and control considerations for high-performance series elastic actuators,” IEEE/ASME Trans. Mechatron. 19(3), 1080–1091 (2013).CrossRefGoogle Scholar
Park, Y., Paine, N. and Oh, S., “Development of force observer in series elastic actuator for dynamic control,” IEEE Trans. Ind. Electron. 65(3), 2398–2407 (2017).CrossRefGoogle Scholar
Li, X., Liu, Y. H. and Yu, H., “Iterative learning impedance control for rehabilitation robots driven by series elastic actuators,” Automatica 90, 1–7 (2018).CrossRefGoogle Scholar
Pérez-Ibarra, J. C., Alarcón, A. L. J., Jaimes, J. C., Ortega, F. M. E., Terra, M. H. and Siqueira, A. A. G., “Design and Analysis of Force Control of a Series Elastic Actuator for Impedance Control of an Ankle Rehabilitation Robotic Platform,” Proceedings of 2017 American Control Conference (ACC) (2017) pp. 2423–2428.Google Scholar
Calanca, A. and Fiorini, P., “Impedance control of series elastic actuators based on well-defined force dynamics,” Robot. Auto. Syst. 96, 81–92 (2017).CrossRefGoogle Scholar
Aguirre-Ollinger, G., “Exoskeleton control for lower-extremity assistance based on adaptive frequency oscillators: Adaptation of muscle activation and movement frequency,” J. Eng. Med. 229(1), 52–68 (2015).CrossRefGoogle ScholarPubMed
Yan, T., Parri, A., Garate, V. R., Cempini, M., Ronsse, R. and Vitiello, N., “An oscillator-based smooth real-time estimate of gait phase for wearable robotics,” Auto. Robots 41(3), 759–774 (2017).CrossRefGoogle Scholar
Kim, J., Lee, G., Heimgartner, R., Revi, D. A., Karavas, N., Nathanson, D., Galiana, I., Eckert-Erdheim, A., Murphy, P., Perry, D., Menard, N., Choe, D. K., Malcolm, P. and Walsh, C. J., “Reducing the metabolic rate of walking and running with a versatile, portable exosuit,” Science 365(6454), 668–672 (2019).CrossRefGoogle ScholarPubMed