Adaptive Proportional-Derivative Sliding Mode Control Law With Improved Transient Performance for Underactuated Overhead Crane Systems

Menghua Zhang; Xin Ma; Rui Song; Xuewen Rong; Guohui Tian; Xincheng Tian; Yibin Li

doi:10.1109/JAS.2018.7511072

Volume 5 Issue 3

May 2018

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2018 > 5(3): 683-690

Menghua Zhang, Xin Ma, Rui Song, Xuewen Rong, Guohui Tian, Xincheng Tian and Yibin Li, "Adaptive Proportional-Derivative Sliding Mode Control Law With Improved Transient Performance for Underactuated Overhead Crane Systems," IEEE/CAA J. Autom. Sinica, vol. 5, no. 3, pp. 683-690, Mar. 2018. doi: 10.1109/JAS.2018.7511072

Citation:

Menghua Zhang, Xin Ma, Rui Song, Xuewen Rong, Guohui Tian, Xincheng Tian and Yibin Li, "Adaptive Proportional-Derivative Sliding Mode Control Law With Improved Transient Performance for Underactuated Overhead Crane Systems," IEEE/CAA J. Autom. Sinica, vol. 5, no. 3, pp. 683-690, Mar. 2018. doi: 10.1109/JAS.2018.7511072

Citation:

Menghua Zhang, Xin Ma, Rui Song, Xuewen Rong, Guohui Tian, Xincheng Tian and Yibin Li, "Adaptive Proportional-Derivative Sliding Mode Control Law With Improved Transient Performance for Underactuated Overhead Crane Systems," IEEE/CAA J. Autom. Sinica, vol. 5, no. 3, pp. 683-690, Mar. 2018. doi: 10.1109/JAS.2018.7511072

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Adaptive Proportional-Derivative Sliding Mode Control Law With Improved Transient Performance for Underactuated Overhead Crane Systems

doi: 10.1109/JAS.2018.7511072

School of Control Science and Engineering, Shandong University, Jinan 250061, China

Funds:

the National High Technology Research and Development Program of China (863 Program) 2015AA042307

Shandong Provincial Scientific and Technological Development Foundation 2014GGX103038

Shandong Provincial Independent Innovation and Achievement Transformation Special Foundation 2015ZDXX0101E01

National Natural Science Fundation of China (NSFC) and Joint Fund of Shandong Province U1706228

the Fundamental Research Funds of Shandong University 2015JC027

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Author Bio:
Menghua Zhang received the M.S. degree at the School of Electrical Engineering and Automation from University of Jinan, China, in 2014. She is currently working toward the Ph.D. degree with the School of Control Science and Engineering, Shandong University, China. Her research interests include control of mechatronics, underacutated overhead crane systems, and bionic eye systems.(e-mail: zhangmenghua@mail.sdu.edu.cn)

Xin Ma received the B.S. degree in industrial automation and the M.S. degree in automation from Shandong Polytechnic University (now Shandong University), China, in 1991 and 1994, respectively. She received the Ph.D. degree in aircraft control, guidance, and simulation from Nanjing University of Aeronautics and Astronautics, China, in 1998. She is currently a Professor at the School of Control Science and Engineering of Shandong University, China. Her current research interests include artificial intelligence, machine vision, human-robot interaction, and mobile robots.(e-mail: maxin@sdu.edu.cn)

Rui Song received the B.S. degree in industrial automation in 1998 and the M.S. degree in control theory and control engineering in 2001 from Shandong University of Science and Technology, and the Ph.D. degree in control theory and control engineering from Shandong University in 2011. He is currently an Associate Professor at the School of Control Science and Engineering of Shandong University, China. He is engaged in research on intelligent sensor network, intelligent robot technology and intelligent control system.(e-mail: rsong@sdu.edu.cn)

Xuewen Rong received the bachelor and master degrees from Shandong University of Science and Technology, China, in 1996 and 1999, respectively. He received the Ph.D. degree from Shandong University, China, in 2013. He is currently a Senior Engineer at the School of Control Science and Engineering of Shandong University, China. His research interests include robotics, mechatronics, and hydraulic servo driving technology.(e-mail: rongxw@sdu.edu.cn)

Guohui Tian is a Professor at the School of Control Science and Engineering of Shandong University, China. And also he is the member of Chinese Association for Artificial Intelligence and International Association for Intelligent Autonomous System. He received the B.S. degree from the Department of Mathematics of Shandong University, China, in 1990, the M.S. degree from the Department of Automation of Shandong University of Technology, China, in 1993, and the Ph.D. degree from the School of Automation, Northeastern University, China, in 1997. He studied as a post-doctoral researcher at the School of Mechanical Engineering of Shandong University from 1999 to 2001, and studied as a Visiting Professor at the Graduate School of Engineering of Tokyo University of Japan from 2003 to 2005. His research interests include service robot, intelligent space, collaboration and cooperation of multi-robot system.(e-mail: g.h.tian @sdu.edu.cn)

Xincheng Tian received the B.S. degree in industrial automation and the M.S. degree in automation from Shandong Polytechnic University (now Shandong University), China, in 1988 and 1993, respectively. He received the Ph.D. degree in aircraft control, guidance, and simulation from Nanjing University of Aeronautics and Astronautics, China, in 2000. He is currently a Professor at the School of Control Science and Engineering of Shandong University, China. His current research interests include robotics, mechatronics, and computer number control (CNC) techniques.(e-mail: txch@sdu.edu.cn)

Yibin Li received the B.S. degree in automation from Tianjin University, China, in 1982, the M.S. degree in electrical automation from Shandong University of Science and Technology, China, in 1990, and the Ph.D. degree in automation from Tianjin University, China, in 2008. From 1982 to 2003, he worked with Shandong University of Science and Technology, China. Since 2003, he has been the Director of Center for Robotics, Shandong University. His research interests include robotics, intelligent control theories, and computer control system.(e-mail: liyb@sdu.edu.cn)
Corresponding author: Xin Ma, e-mail: maxin@sdu.edu.cn
Received Date: 2017-04-19
Accepted Date: 2017-08-30

Abstract

Abstract

In this paper, an adaptive proportional-derivative sliding mode control (APD-SMC) law, is proposed for 2D underactuated overhead crane systems. The proposed controller has the advantages of simple structure, easy to implement of PD control, strong robustness of SMC with respect to external disturbances and uncertain system parameters, and adaptation for unknown system dynamics associated with the feedforward parts. In the proposed APD-SMC law, the PD control part is used to stabilize the controlled system, the SMC part is used to compensate the external disturbances and system uncertainties, and the adaptive control part is utilized to estimate the unknown system parameters. The coupling behavior between the trolley movement and the payload swing is enhanced and, therefore, the transient performance of the proposed controller is improved. The Lyapunov techniques and the LaSalle's invariance theorem are employed in to support the theoretical derivations. Experimental results are provided to validate the superior performance of the proposed control law.
- Adaptability,
- adaptive proportional-derivative sliding mode control (APD-SMC),
- coupling behavior,
- LaSalle's invariance theorem,
- Lyapunov techniques,
- robustness,
- underactuated overhead crane

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References(46)

References

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Adaptive Proportional-Derivative Sliding Mode Control Law With Improved Transient Performance for Underactuated Overhead Crane Systems

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