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Original Articles

Adaptive control of a class of quantised nonlinearly parameterised systems with unknown control directions

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Pages 941-951 | Received 25 Feb 2016, Accepted 03 Aug 2016, Published online: 25 Aug 2016
 

ABSTRACT

The problem of adaptive control is studied for a class of nonlinearly parameterised systems with quantised input signal and unknown control directions. The homogeneous domination approach and the Nussbaum-type gain method are applied to design an adaptive state-feedback controller. A hysteretic type of quantiser is incorporated to reduce actuator chattering. The proposed controller can ensure that all signals of the nonlinear system are globally bounded, and that the system state asymptotically converges to zero. Two numerical examples are presented to demonstrate the effectiveness and potential of the proposed techniques.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was partially supported by China Scholarship Council [201406840036].

Notes on contributors

Wenhui Liu

Wenhui Liu received her B.S. degree in information and computing science from Nanjing University of Science and Technology, China, in 2012. She is currently working toward the Ph.D. degree with the School of Automation, Nanjing University of Science and Technology. From December 2014 to June 2016, she was a joint supervisory Ph.D. student in the School of Electrical and Electronic Engineering at the University of Adelaide, Australia. Her research interests include adaptive control, fuzzy control, and quantised control of nonlinear systems.

Cheng-Chew Lim

Cheng-Chew Lim (M'82SM'02) received his B.Sc. (Hons.) and Ph.D. degrees from Loughborough University, Leicestershire, UK. His research interests include control and systems theory, machine learning and optimisation techniques. Dr Lim is a reader and associate professor in electrical and electronic engineering, and head of the School of Electrical and Electronic Engineering, The University of Adelaide, Australia. He is serving as an editorial board member for the Journal of Industrial and Management Optimization and has served as a guest editor of a number of journals, including Discrete and Continuous Dynamical System-Series B. Currently, he is the chair of the IEEE Chapter on the IEEE Chapter on Control and Aerospace Electronic Systems in the IEEE South Australia Section.

Shengyuan Xu

Shengyuan Xu received his B.Sc. degree from the Hangzhou Normal University, China, in 1990, M.Sc. degree from the Qufu Normal University, China, in 1996, and Ph.D. degree from the Nanjing University of Science and Technology, China, 1999. From 1999 to 2000, he was a research associate in the Department of Mechanical Engineering at the University of Hong Kong, Hong Kong. From December 2000 to November 2001, and December 2001 to September 2002, he was a postdoctoral researcher in CESAME at the Universit catholique de Louvain, Belgium, and the Department of Electrical and Computer Engineering at the University of Alberta, Canada, respectively. From September 2002 to September 2003, and September 2003 to September 2004, he was a William Mong Young Researcher and an Honorary Associate Professor, respectively, both in the Department of Mechanical Engineering at the University of Hong Kong, Hong Kong. Since November 2002, he has joined the School of Automation at the Nanjing University of Science and Technology as a professor. Dr Xu was a recipient of the National Excellent Doctoral Dissertation Award in the year 2002 from the Ministry of Education of China. He obtained a grant from the National Science Foundation for Distinguished Young Scholars of P.R. China in 2006. He was awarded a Cheung Kong Professorship in 2008 from the Ministry of Education of China. Dr Xu is a member of the Editorial Boards of the Transactions of the Institute of Measurement and Control, and the International Journal of Control, Automation, and Systems. His current research interests include robust filtering and control, singular systems, time-delay systems, neural networks, multidimensional systems and nonlinear systems.

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