Event-triggered based adaptive neural network control of a robotic manipulator with output constraints and disturbance

Abstract

This paper studies event-triggered based adaptive neural network (NN) tracking control of a robotic manipulator with output constraints and disturbance. First, a novel asymmetric tan-type barrier Lyapunov function (BLF) is developed to satisfy the requirement of time-varying output constraints. Then, a fixed threshold event triggering is proposed to reduce the energy consumption, which avoids the happening of Zeno behaviour after analysis. Further, a disturbance observer (DO) and an adaptive neural network are devised to estimate the bounded disturbance and the unknown dynamics of the robotic manipulator. The proposed controller can achieve uniform boundness of the solution and adjustment of transient performance. Finally, the effectiveness of the presented methods is verified by related simulation results.

Keywords:

• Event triggering
• adaptive neural network control
• disturbance observer
• barrier Lyapunov function
• output constraints

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Xuechao Qiu

Xuechao Qiu received the B.S. and M.S. degree in electrical engineering from the Yanshan University, Qinhuangdao, China, in 2017 and 2020, respectively. He is currently working towards his Ph.D. in Southeast University, Nanjing, China. His current research interests include distributed cooperative control of micro-grid systems and anti-disturbance control.

Changchun Hua

Changchun Hua received the Ph.D degree in electrical engineering from Yanshan University, Qinhuangdao, China, in 2005. He was a research Fellow in National University of Singapore from 2006 to 2007. From 2007 to 2009, he worked in Carleton University, Canada, funded by Province of Ontario Ministry of Research and Innovation Program. From 2009 to 2011, he worked in University of Duisburg-Essen, Germany, funded by Alexander von Humboldt Foundation. Now he is a full Professor in Yanshan University,China. He is the author or coauthor of more than 110 papers in mathematical, technical journals, and conferences. He has been involved in more than 10 projects supported by the National Natural Science Foundation of China, the National Education Committee Foundation of China, and other important foundations. His research interests are in nonlinear control systems, control systems design over network, teleoperation systems and intelligent control.

Jiannan Chen

Jiannan Chen received his B.E. degree in mechanical engineering and automation from Beijing Union University, Beijing, China in 2015. He received an M.Tech with specialisation in Control Systems from Yan Shan University, Hebei, China in 2017. He received his Ph.D. degree in electrical engineering from Yanshan University, Hebei, China, in 2020. His research interests include nonlinear control, sliding mode control, constrained control, finite and fixed time control design.

Yu Zhang

Yu Zhang received his Ph.D. degree in electrical engineering from Yanshan University, Qinhuangdao, China, in 2019. He is currently working in Yanshan University. His current research interests include visual servoing control, robust control, and nonlinear system control.

Xinping Guan

Xinping Guan received the B.S. degree in mathematics from Harbin Normal University, Harbin, China, in 1986, and the M.S. degree in applied mathematics and the Ph.D. degree in electrical engineering from the Harbin Institute of Technology, Harbin, in 1991 and 1999, respectively. He is with the Department of Automation, Shanghai Jiao Tong University, Shanghai, China. He has co-authored over 200 papers in mathematical, technical journals, and conferences. As (a)an (Co)-Investigator, he has finished over 20 projects supported by the National Natural Science Foundation of China, the National Education Committee Foundation of China, and other important foundations. He is a Cheung Kong Scholars Programme Special Appointment Professor. His current research interests include networked control systems, robust control and intelligent control for complex systems and their applications. Dr. Guan is serving as a Reviewer of Mathematic Review of America, a member of the Council of Chinese Artificial Intelligence Committee, and the Chairman of Automation Society of Hebei Province, China.