Novel observer design method for Lur'e differential inclusion systems

Abstract

This paper proposes a new method to design observers for Lur'e differential inclusion systems. The feature of this method is that the designed observers do not contain any set-valued functions. single-input-single-output (SISO) systems are considered firstly, then the results are extended to multiple-input-multiple-output (MIMO) systems. For MIMO systems, the form of reduced-order observers is also presented. Simulations are given to show these observers work well.

Keywords:

• Lur'e differential inclusion systems
• set-valued functions
• observers

Additional information

Funding

The authors are grateful to the National Natural Science Foundation of China [grant number 61403267], [grant number 61403268]; Natural Science Foundation of Jiangsu Province of China [grant number BK20130322], [grant number BK20130331]; Natural Science Fund for Colleges and Universities in Jiangsu Province [grant number 13KJB510032]; China Postdoctoral Science Foundation [grant number 2013M530268], [grant number 2013M541720], [grant number 2013M531401]; and the Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China [grant number ICT1435].

Notes on contributors

Jun Huang

Jun Huang was born in Anhui Province, China, in 1984. He obtained his M.S. degree in Mathematics from East China Normal University in 2008 and his Ph.D. degree in Automation from Shanghai Jiao Tong University in 2012. He is now a Lecturer in the School of Mechanical and Electrical Engineering, Soochow University. His current research interests include differential inclusion system, the theory of observer design, nonlinear control, adaptive control.

Yu Gao

Yu Gao received the Ph.D. degree in Electronics and Information Engineering from Chonbuk National University, Korea, in 2012. Currently, he is a Lecturer at the School of Mechanical and Electrical Engineering, Soochow University. His research interests are in the areas of the model predictive control, robust optimal control, and robotics.

Lei Yu

Lei Yu was born in Xuancheng, P.R. China, 1983. He received the M.S. degree in Control Theory and Control Engineering from Hefei University of Technology, China in 2008 and the Ph.D. degree in Automatic Control Theory and Applications from Southeast University in 2011. He is now an associate professor in the College of Mechanical and Electric Engineering, Soochow University. His research interests are in switched nonlinear systems, robust adaptive control, neural network control, etc.