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Speed tracking and nonlinear disturbance rejection of PM synchronous motor by internal model design

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Abstract

This paper studies a speed tracking and nonlinear disturbance rejection problem of PM synchronous motor. By formulating the problem as a robust output regulation problem of multivariable nonlinear system, we propose a robust output feedback control law based on internal model design. It is worth mentioning that the control law, can not only achieve asymptotic tracking of desired speed, but also reject nonlinear external disturbance in the load torque, generated by a so-called nonlinear exosystem. Simulation results will also be provided to demonstrate the effectiveness of our design.

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Correspondence to Zhaowu Ping.

Additional information

Recommended by Associate Editor M. Chadli under the direction of Editor Hamid Reza Karimi. This work has been supported by the National Natural Science Foundation of China (Grant no. 61403117, 61573126, 61374030, 61533012), the Fundamental Research Funds for the Central Universities (Grant no. JZ2017HGTB0194, 2014HGQC0013), and Project funded by China Postdoctoral Science Foundation (Grant no. 2016M602005).

Zhaowu Ping received his B.E. degree from Shanghai Maritime University in 2005, M.E. degree from Shanghai Jiao Tong University in 2008. Then he worked in Bayer Technology & Engineering (Shanghai) Company Limited as DCS Engineer for three months. He received his Ph.D. degree from Chinese University of Hong Kong in 2011. From 2012 to 2013, he was with Seoul National University as postdoctoral researcher. Since 2013, he is with Hefei University of Technology as associate professor. His major research interests include nonlinear output regulation theory and applications, electromechanical system control, neural network control, control and estimation of switched systems.

Qingchuan Ma received her B.E. degree from Liaoning Shihua University in 2013. She is currently working toward an M.E. degree in School of Electrical Engineering and Automation, Hefei University of Technology. Her research interests include nonlinear output regulation theory and applications, electromechanical system control.

Hao Tang received his B.E. degree from Anhui Institute of Technology, China in 1995, an M.E. degree from the Institute of Plasma Physics, Chinese Academy of Sciences in 1998 and his Ph.D. degree from University of Science and Technology of China in 2002. He has been a postdoctoral researcher in The University of Tokyo, Japan, from 2005 to 2007, and a JSPS fellow in Kanagawa University, Japan, from January to March in 2013. He is a recipient of the 8th HO PAN QING YI best paper award in DEDS field in the year 2010. He is currently a Professor at the Hefei University of Technology, China. His research interests include discrete event dynamic systems (DEDSs), intelligent production systems, smart grid, reinforcement learning, and neuro-dynamic programming.

Qi Tan received his Ph.D. degree from School of Computer Science and Technology, University of Science and Technology of China in 2012. He is now a Lecturer at School of Electrical Engineering and Automation, Hefei University of Technology. His major research interests include production scheduling, stochastic processes, the methodology of neuro-dynamic programming, intelligent optimization.

Jun-Guo Lu received his B.E. and Ph.D. degrees in control theory and control engineering from Nanjing University of Science and Technology, in 1997 and 2002, respectively. From 2001 to 2003, he was with the Department of Automation, Shanghai Jiao Tong University as a postdoctoral fellow. Then he joined the Shanghai Jiao Tong University in 2003, where currently he is a professor in Department of Automation. His major research interests include nonlinear output regulation theory and applications, fractional-order control system, robot control and multi robot coordination, complex networks, big data, 3D digitalization.

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Ping, Z., Ma, Q., Tang, H. et al. Speed tracking and nonlinear disturbance rejection of PM synchronous motor by internal model design. Int. J. Control Autom. Syst. 15, 1684–1692 (2017). https://doi.org/10.1007/s12555-016-0288-z

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  • DOI: https://doi.org/10.1007/s12555-016-0288-z

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