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On the Disturbance Rejection Control of Flexible-joint Robot: A GPIO-based Approach

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  • Robot and Applications
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Abstract

A robust disturbance rejection control scheme is addressed for the trajectory tracking problem of a flexible-joint robot (FJR). The system is always severely affected by various types of unknown disturbances including model errors, couplings, changing working environments as well as unmodeled dynamics. These disturbances on the link and actuator side will deteriorate the control performance of FJR. By considering all the disturbances as an unknown lumped time-varying disturbance, a flatness description of FJR is developed. Then, a new output feedback controller is constructed through the estimates of unmeasurable states and unknown lumped disturbance provided by a generalized proportional integral observer (GPIO). The stability of the closed-loop system with the driven of the proposed control scheme is guaranteed under some mild assumptions. Compared with the conventional linear active disturbance rejection control (LADRC) scheme, test results are presented to demonstrate the feasibility and efficacy of the proposed control approach.

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Authors and Affiliations

  1. Key Laboratory of Industrial Internet of Things & Networked Control, Ministry of Education, and Chongqing Key Laboratory of Complex Systems and Bionic Control, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Huiming Wang, Yang Zhang, Xiaolei Chen & Xianlun Tang

  2. School of Mechanical and Aerospace Engineering & Robotics Research Centre (RRC), Nanyang Technological University, 639798, Singapore, Singapore

    Huiming Wang & I-Ming Chen

Authors
  1. Huiming Wang
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  2. Yang Zhang
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  3. Xiaolei Chen
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  4. Xianlun Tang
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  5. I-Ming Chen
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Correspondence to Huiming Wang.

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Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This work was supported in part by National Natural Science Foundation of China (61803059, 61673079), in part by the Innovation Research Group of Universities in Chongqing, China, in part by National Key Research and Development Program of China (2018YFB1702200), and in part by National Robotics Program, RDS, SERC, Singapore (1922200001).

Huiming Wang received his Ph.D. degree from Southeast University, Nanjing, China, in 2016. He is currently an Associate Professor with the School of Automation, Chongqing University of Posts and Telecommunications, Chongqing, China, and a Research Fellow with the School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore. His research interests include the design and applications of advanced control techniques to robotic and mechatronic systems such as high-performance servo drives, industrial robots, and compliant robots.

Yang Zhang received his B.S. degree from Linyi University, Shandong, China, in 2019. He is currently pursuing an M.E. degree in control theory and control engineering from Chongqing University of Posts and Telecommunications, Chongqing, China. His research interests include the design and applications of advanced control techniques to robotic systems.

Xiaolei Chen received his B.S. degree from Qingdao University of Science and Technology, Qingdao, China, in 2002, an M.S. degree from Taiyuan University of Technology, Taiyuan, China, in 2007, and a Ph.D. degree in control theory and control engineering from Northwestern Polytechnical University, Xi’an, in 2016. He is currently a lecturer with the School of Automation, Chongqing University of Posts and Telecommunications, Chongqing, China. His research interests include control theory and image processing.

Xianlun Tang received his M.S. and Ph.D. degrees in control theory and control engineering from Chongqing University, Chongqing, China, in 2002 and 2007, respectively. He is currently a Professor with the Chongqing University of Posts and Telecommunications, Chongqing, China. His current research interests include intelligent system and robot, and the theory and application of pattern recognition.

I-Ming Chen received his B.S. degree from National Taiwan University, Taipei, Taiwan, in 1986, and his M.S. and Ph.D. degrees from the California Institute of Technology, Pasadena, in 1989 and 1994, respectively. He has been with the School of Mechanical and Aerospace Engineering of Nanyang Technological University (NTU) in Singapore since 1995. He was a Japan Society for the Promotion of Science (JSPS) Visiting Scholar at Kyoto University, Kyoto, Japan in 1999, a Visiting Scholar in the Department of Mechanical Engineering, Massachusetts Institute of Technology (MIT), in 2004. He was Director of Robotics Research Centre (2013 to 2017), and Director of Intelligent Systems (2006 to 2015) in NTU. His research interests are in construction and logistics robots, wearable devices, human-robot interaction and industrial automation. Professor Chen was General Chairman of 2017 IEEE International Conference on Robotics and Automation (ICRA 2017) in Singapore, Fellow of ASME, and Fellow of Academy of Engineering, Singapore. He is the Editor-in-Chief of IEEE/ASME Transactions on Mechatronics from 2020 to 2022.

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Wang, H., Zhang, Y., Chen, X. et al. On the Disturbance Rejection Control of Flexible-joint Robot: A GPIO-based Approach. Int. J. Control Autom. Syst. 19, 2910–2920 (2021). https://doi.org/10.1007/s12555-020-492-8

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  • DOI: https://doi.org/10.1007/s12555-020-492-8

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