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Regulation Control for Discrete-time Stochastic Nonlinear Active Suspension

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  • Control Theory and Applications
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Abstract

The regulation problem of discrete-time stochastic nonlinear active suspension is considered in this paper. Firstly, a stability theorem of practically stable in the mean square sense for discrete-time stochastic systems is given. Secondly, the nonlinear active suspension subject to random disturbances modeled by the stochastic difference equation is obtained by the Euler-Maruyama approximation. Thirdly, a state feedback controller is worked out by a discrete backstepping approach such that the states of the discrete-time stochastic nonlinear active suspension can be regulated to a neighbourhood of zero. Finally, the efficiency can be verified by the simulation results.

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Funding

This work was supported by the National Natural Science Foundation of China (No. 61973198, 61973148), the Research Fund for the Taishan Scholar Project of Shandong Province of China, SDUST Research Fund (No.2015TDJH105).

Author information

Authors and Affiliations

  1. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, Shandong Province, 266590, China

    Likang Feng & Weihai Zhang

  2. College of Mathematics, Shandong University, Jinan, Shandong Province, 250100, China

    Xiaoyu Zhao

  3. School of Mathematics Science, Liaocheng University, Liaocheng, 252000, China

    Jianwei Xia

  4. School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China

    Yajuan Liu

Authors
  1. Likang Feng
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  2. Xiaoyu Zhao
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  3. Weihai Zhang
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  4. Jianwei Xia
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  5. Yajuan Liu
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Corresponding author

Correspondence to Weihai Zhang.

Additional information

Likang Feng received his M.S. degree in operations research and cybernetics, from Yantai University, Yantai, China in 2015. From 2019 to 2020, he was a visiting scholar with the Department of Electrical Engineering, Yeungnam University, Gyeongsan, Korea. He is currently pursuing a Ph.D. degree in control theory and control engineering from Shandong University of Science and Technology, Qingdao, China. His research interests include random impulsive system, stochastic stability analysis, and nonlinear stochastic control.

Xiaoyu Zhao received his B.S. degree in basic and applied mathematics from the University of Science and Technology of China, Hefei, China, in 2011. He is currently pursuing an M.S. degree with the College of Mathematics, Shandong University, Jinan, China. His research interests include bioinformatics, control theory, and deep-learning.

Weihai Zhang received his M.S. degree in probability theory and mathematical statistics from Hangzhou University (currently, Zhejiang University), and his Ph.D. degree in operations research and cybernetics from Zhejiang University, Hangzhou, China, in 1994 and 1998, respectively. He is currently a Professor at Shandong University of Science and Technology. He is a Taishan Scholar of Shandong Province of China, and serves as an Associate Editor for Asian Journal of Control and Journal of the Franklin Institute. He has published more than 110 peer-reviewed journal papers and one monograph (W. Zhang, L. Xie, B. S. Chen. Stochastic H2/H∞ Control: A Nash Game Approach, Boca Raton, FL, USA: CRC Press, 2017). His research interests include linear and nonlinear stochastic optimal control, mean-field systems, robust H∞ control, stochastic stability and stabilization, multi-objective optimization, fuzzy adaptive control. He is a Member of Technical Committee on Control Theory of Chinese Association of Automation. He received the second prize of the Ministry of Education of the People’s Republic of China twice.

Jianwei Xia is a professor of the School of Mathematics Science, Liaocheng University. He received his Ph.D. degree in automatic control from Nanjing University of Science and Technology in 2007. From 2010 to 2012, he worked as a Postdoctoral Research Associate in the School of Automation, Southeast University, Nanjing, China. From 2013 to 2014, he worked as a Postdoctoral Research Associate in the Department of Electrical Engineering, Yeungnam University, Kyongsan, Korea. His research topics are robust control, stochastic systems and neural networks.

Yajuan Liu received her B.S. degree in mathematics and applied mathematics from Shanxi Normal University, Linfen, China, in 2010, an M.S. degree in applied mathematics from the University of Science and Technology Beijing, Beijing, China, in 2012, and a Ph.D. degree from the Division of Electronic Engineering, Daegu University, Daegu, Korea, in 2015. From 2015 to 2018, she was a Post-doctoral Research Fellow with the Department of Electrical Engineering, Yeungnam University, Gyeongsan, Korea. She is currently an Associate Professor with the School of Control and Computer Engineering, North China Electric Power University, Beijing. Her research focus is on control of dynamic systems, including neural networks and complex systems.

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Feng, L., Zhao, X., Zhang, W. et al. Regulation Control for Discrete-time Stochastic Nonlinear Active Suspension. Int. J. Control Autom. Syst. 20, 888–896 (2022). https://doi.org/10.1007/s12555-020-0535-1

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  • DOI: https://doi.org/10.1007/s12555-020-0535-1

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