Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots: A Barrier Function Sliding Mode Approach

Yunjun Zheng; Jinchuan Zheng; Ke Shao; Han Zhao; Hao Xie; Hai Wang

doi:10.1109/JAS.2023.124002

Volume 11 Issue 4

Apr. 2024

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2024 > 11(4): 1007-1021

Y. Zheng, J. Zheng, K. Shao, H. Zhao, H. Xie, and H. Wang, “Adaptive trajectory tracking control for nonholonomic wheeled mobile robots: A barrier function sliding mode approach,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 4, pp. 1007–1021, Apr. 2024. doi: 10.1109/JAS.2023.124002

Citation:

Y. Zheng, J. Zheng, K. Shao, H. Zhao, H. Xie, and H. Wang, “Adaptive trajectory tracking control for nonholonomic wheeled mobile robots: A barrier function sliding mode approach,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 4, pp. 1007–1021, Apr. 2024. doi: 10.1109/JAS.2023.124002

Citation:

Y. Zheng, J. Zheng, K. Shao, H. Zhao, H. Xie, and H. Wang, “Adaptive trajectory tracking control for nonholonomic wheeled mobile robots: A barrier function sliding mode approach,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 4, pp. 1007–1021, Apr. 2024. doi: 10.1109/JAS.2023.124002

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Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots: A Barrier Function Sliding Mode Approach

doi: 10.1109/JAS.2023.124002

Funds: This work was supported in part by the China Scholarship Council (202106690037) and the Natural Science Foundation of Anhui Province (19080885QE194)

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Author Bio:
Yunjun Zheng received the B.Eng. degree in mechanical design and manufacture and automation from Hefei University of Technology in 2017, where he is currently pursuing the Ph.D. degree in mechanical manufacture and automation. He is currently a Visiting Scholar with the Swinburne University of Technology, Australia. His research interests include adaptive robust control, fuzzy optimization, sliding mode control, and robotic control

Jinchuan Zheng (Senior Member, IEEE) received the B.Eng. and M.Eng. degrees in mechatronics engineering from Shanghai Jiao Tong University in 1999 and 2002, respectively, and the Ph.D. degree in electrical and electronic engineering from Nanyang Technological University, Singapore in 2006. In 2005, he joined the Australian Research Council (ARC) Centre of Excellence for Complex Dynamic Systems and Control, School of Electrical and Computer Engineering, the University of Newcastle, Callaghan, Australia, as a Research Academic. From 2011 to 2012, he was a Staff Engineer with the Western Digital Hard Disk Drive R&D Center, Singapore. Since 2012, he has been with Swinburne University of Technology, Australia. He is currently an Associate Professor with the School of Science, Computing and Engineering Technologies. His research interests include high-precision motion control systems, electric vehicle control technology, mobile robots, and biomechatronic devices

Ke Shao (Member, IEEE) received the B.E. and Ph.D. degrees in mechanical engineering from Hefei University of Technology in 2013 and 2019, respectively. From 2017 to 2019, he was a Visiting Scholar at Swinburne University of Technology, Australia, founded by China Scholarship Council. From 2019 to 2023, he was the Postdoctor and then the Research Assistant at Tsinghua Shenzhen International Graduate School, Tsinghua University. Currently, he works as the Associate Professor at the School of Civil Aviation, Northwestern Polytechnical University. His research interests include dynamics, nonlinear control, sliding mode control, robots, high-precision control, and vehicle dynamics and control

Han Zhao received the Ph.D. degree in mechanical engineering from Aalborg University, Denmark, in 1990. He is currently a Professor with the Hefei University of Technology. His research interests include mechanical transmission, magnetic machine, vehicles, digital design and manufacturing, information system, dynamics, and control

Hao Xie received the B.Eng. degree in robotics and mechatronics and the Ph.D. degree in control science and engineering from the School of Software and Electrical Engineering, Swinburne University of Technology, Australia, in 2019 and 2023, respectively. He is currently an Engineer with the Shanghai Aerospace Control Technology Institute, and a Postdoctoral Fellow with the School of Automation Science and Electrical Engineering, Beihang University. His research interests include trajectory tracking and cooperative guidance of aerial and ground vehicles

Hai Wang (Senior Member, IEEE) received the B.Eng. degree in electrical and electronic engineering from Hebei Polytechnic University in 2007, the M.E. degree in electrical and electronic engineering from Guizhou University in 2010, and the Ph.D. degree in electrical and electronic engineering from the Swinburne University of Technology, Australia, in 2013. From 2014 to 2015, he was a Postdoctoral Research Fellow with the Faculty of Science, Engineering, and Technology, Swinburne University of Technology, Australia. From 2015 to 2019, he was a Professor with the School of Electrical Engineering and Automation, Hefei University of Technology. He is currently a Senior Lecturer of electrical engineering and a Deputy Academic Chair of Instrumentation and Control Engineering and Industrial Computer Systems Engineering with the College of Science, Health, Engineering and Education, Murdoch University, Australia. His current research interests include sliding mode control, adaptive control, robotics and mechatronics, neural networks, nonlinear systems, and vehicle dynamics and control
Corresponding author: Ke Shao, e-mail: kshao@nwpu.edu.cn
Received Date: 2023-05-30
Revised Date: 2023-07-25
Accepted Date: 2023-10-05

Available Online: 2023-12-13

Abstract

Abstract

The trajectory tracking control performance of nonholonomic wheeled mobile robots (NWMRs) is subject to nonholonomic constraints, system uncertainties, and external disturbances. This paper proposes a barrier function-based adaptive sliding mode control (BFASMC) method to provide high-precision, fast-response performance and robustness for NWMRs. Compared with the conventional adaptive sliding mode control, the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds. Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function. The benefit is that the overestimation of control gain can be eliminated, resulting in chattering reduction. Moreover, a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator. The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the pre-specified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.
- Adaptive sliding mode,
- barrier function,
- nonholonomic wheeled mobile robot (NWMR),
- trajectory tracking control

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The finite-time control with predefined precision for nonholonomic wheeled mobile robot with uncertainties is achieved
The proposed method eliminates the requirements for uncertainty bounds and guarantees the non-overestimation for control gain
The actuator saturation issue is prevented by introducing a modified barrier function-like control gain with specified performance

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots: A Barrier Function Sliding Mode Approach

doi: 10.1109/JAS.2023.124002

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