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Model Identification and Human-robot Coupling Control of Lower Limb Exoskeleton with Biogeography-based Learning Particle Swarm Optimization

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  • Robot and Applications
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Abstract

Lower limb exoskeleton is a typical wearable robot to assist human motion and improve physiological power. However, the control performance and stability are affected by some unknown model parameters and control algorithms. Therefore, it is necessary to investigate the model parametric identification and the control design of lower extremity exoskeleton. Firstly, the two degree-of-freedom (DoF) exoskeleton model is constructed by the Lagrange technique. Then the biogeography-based learning particle swarm optimization (BLPSO) is used to optimize the B-spline function parameters and the smooth stimulated trajectories is designed. Meanwhile, the BLPSO is also adopted to identify unknown model parameters of the exoskeleton based on the torques and the joint angles. To decline the negative effect of parametric identification error of exoskeleton, the passive backstepping controller is proposed to improve the tracking performance of human-robot motion. Furthermore, the active admittance controller is adopted to improve the motion comfort of tester. Finally, the comparative experimental results are verified on the platform, which show the BLPSO algorithm has better parametric identification accuracy than PSO and GA. Furthermore, the comparative results have verified that the proposed controller can improve the tracking behavior and reduce the human-robot interaction torque in wearable motion.

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Funding

This work was supported by National Natural Science Foundation of China (Grant Nos. 51775089, 52175046, 51975024, and 12072068), Sichuan Science and Technology Program (Grant Nos. 22CXRC0089 and 22ZDYF3178).

Author information

Authors and Affiliations

  1. School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Qing Guo, Zhenlei Chen, Yao Yan & Wenying Xiong

  2. Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province, Chengdu, 611731, China

    Qing Guo, Zhenlei Chen, Yao Yan & Wenying Xiong

  3. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Dan Jiang

  4. School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing, China

    Yan Shi

Authors
  1. Qing Guo
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  2. Zhenlei Chen
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  3. Yao Yan
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  4. Wenying Xiong
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  5. Dan Jiang
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Corresponding authors

Correspondence to Qing Guo or Yan Shi.

Additional information

Qing Guo received his B.E. degree in automation from Harbin Institute of Technology, Harbin, China, in 2003, and his M.S. and Ph.D. degrees in navigation, guidance and control from Harbin Institute of Technology, in 2005 and 2008, respectively. Now he is a full professor in School of Aeronautics and Astronautics, University of Electronic Science and Technology of China. He is also the backup candidates for academic and technical leaders in Sichuan Province, the member of Fluid transmission and control branch, Chinese Mechanical Engineering Society, the Senior member of Mechanical Engineering Society, Youth expert group leader of the committee on fluid control and Engineering, Chinese society of mechanics. From December 2013 to December 2014, he was an academic visitor with Center for Power Transmission and Motion Control, Department of Mechanical Engineering, University of Bath, UK. He serves as a guest editor of Chinese Journal of Mechanical Engineering (English Edition). His research interests include robust and adaptive control, electrohydraulic, and exoskeleton robot.

Zhenlei Chen received his B.E. degree in automation from Zhoukou Normal University, Zhoukou, China, in 2015, and an M.E. degree in navigation, guidance and control from University of Electronic Science and Technology of China, in 2018. Now he is a currently a Ph.D. student in the School of Aeronautics and Astronautics, University of Electronic Science and Technology of China. His current research interests include nonlinear control, mechatronics and robotics.

Yao Yan received his Ph.D. degree in Mechanics in 2014 from Tongji University, Shanghai, China. Now he is an Associate Professor of the School of Aeronautics and Astronautics, University of Electronics Science and Technology of China. His research interests include regenerative cutting chatter and control for suppression, vibro-impact capsule robot, control of multistability, and exoskeleton robot.

Wenying Xiong received his B.E. degree in measurement, control technology and instruments from Guilin University of Electronic Technology, China, in 2017, and an M.E. degree in Navigation, Guidance and Control from University of Electronic Science and Technology of China, in 2020. Now he works in Huawei Technologies Co., Ltd. His current research interests include embedded systems and mechatronics.

Dan Jiang received her B.E. degree in mechanical engineering from Harbin Institute of Technology, Harbin, China, in 2002, and her M.S. and Ph.D. degrees in fluid power transmission and control from Harbin Institute of Technology, in 2005 and 2009, respectively. Since April 2009, she has been with School of Mechanical, Electronic and Industrial Engineering, University of Electronic Science and Technology of China, Chengdu, China, where she became a lecturer. Since June 2013, she became an associate professor in School of Mechanical, Electronic and Industrial Engineering. Her research interests include fluid transmission and control system, pneumatic system, microfluidic technology, and mechanical reliability.

Yan Shi is a full professor of the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. He received his doctoral degree in mechanical engineering from Beihang University. He received the Top young talents of national ten thousand talents plan in 2018, and won the second prize of National Science and Technology Progress Award in 2017. From 2013 to 2019, he won three times of the First and Second prize of Machinery Industry Federation. His research interests include mechatronic engineering, intelligent medical devices and energy-saving technologies of pneumatic systems.

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Guo, Q., Chen, Z., Yan, Y. et al. Model Identification and Human-robot Coupling Control of Lower Limb Exoskeleton with Biogeography-based Learning Particle Swarm Optimization. Int. J. Control Autom. Syst. 20, 589–600 (2022). https://doi.org/10.1007/s12555-020-0632-1

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  • DOI: https://doi.org/10.1007/s12555-020-0632-1

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