An adaptive fault-tolerant control scheme for a class of fractional-order systems with unknown input dead-zones

Abstract

An adaptive backstepping fault-tolerant control scheme is presented for a class of fractional-order systems in the presence of unknown input dead-zones. The proposed fault-tolerant control scheme ensures all the closed-loop signals are bounded ultimately. Especially, the tracking error can be made as small as possible by choosing appropriate design parameters. Furthermore, this scheme not only works for fractional-order systems with unknown linear terms but also works for these with unknown nonlinear terms. Finally, several practical examples are simulated to verify the effectiveness of the proposed fault-tolerant control scheme.

Keywords:

• Fractional-order systems
• backstepping control
• fault-tolerant
• unknown input dead-zone
• unknown terms

Disclosure statement

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

Additional information

Funding

This work is financially sponsored by the Natural Sciences and Engineering Research Council of Canada (NSERC), Taishan Scholar Project of Shandong Province of China (201812093, 2015162), the National Natural Science Foundation of China (61773072, 61803228) and Ph.D. Foundation Research Project of Shandong Jianzhu University (X18083Z).

Notes on contributors

Caiyun Wang

Caiyun Wang received her B.Sc. degree in Mathematics from Shandong Normal University, Jinan, China in 2013, the Ph.D. degree in system science from Chinese Academy of Sciences, Beijing, China in 2018. Since 2018, she has been a Lecturer in Shandong Jianzhu University, Jinan, China. Her research interests are control of nonlinear systems and intervention of multi-agent systems.

Xiaoping Liu

Xiaoping Liu received his B.Sc., M.Sc., and Ph.D. degrees from Northeastern University, PR China, in 1984, 1987, and 1989, respectively. He spent more than 10 years with the School of Information Science and Engineering at Northeastern University, PR China. In 2001, he joined the Department of Electrical Engineering at Lakehead University, Canada. Since 2017, he has been a visiting professor in Shandong Jianzhu University, Jinan, China. His research interests are nonlinear control systems, singular systems, and adaptive control. He is a member of the Professional Engineers of Ontario.

Huanqing Wang

Huanqing Wang received the B.Sc. degree in mathematics from Bohai University, Jinzhou, China, in 2003, the M.Sc. degree in Mathematics from Inner Mongolia University, Huhhot, China, in 2006, and the Ph.D. degree from the Institute of Complexity Science, Qingdao University, Qingdao, China, in 2013. He was a Post-Doctoral Fellow with the Department of Electrical Engineering, Lakehead University, Thunder Bay, ON, Canada, in 2014, and was a Post-Doctoral Fellow with the Department of Systems and Computer Engineering, Carleton University, Ottawa, ON Canada. He has authored or co-authored over 50 papers in top international journals. His current research interests include adaptive backstepping control, fuzzy control, neural networks control, and stochastic nonlinear systems. He serves as an Associate Editor for several journals, including Neural Computing and Applications, International Journal of Control, Automation, and Systems, and IEEE ACCESS.