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Modified stochastic gradient parameter estimation algorithms for a nonlinear two-variable difference system

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  • Control Theory and Applications
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Abstract

This paper proposes a stochastic gradient algorithm and two modified stochastic gradient algorithms for a nonlinear two-variable difference system. The output and the input of a two-variable parameter system depend on time and on spatial coordinates. A stochastic gradient algorithm is introduced to estimate the unknown parameters. In order to increase the convergence rate but not to increase the computational effort, two modified stochastic gradient algorithms are also proposed. The simulation results indicate that the proposed methods are effective.

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Author information

Authors and Affiliations

  1. Wuxi Professional College of Science and Technology, Wuxi, 214122, P. R. China

    Jing Chen

  2. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, P. R. China

    Bin Jiang

Authors
  1. Jing Chen
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  2. Bin Jiang
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Corresponding author

Correspondence to Bin Jiang.

Additional information

Recommended by Associate Editor Xiaojie Su under the direction of Editor Duk-Sun Shim. This work was supported by the National Natural Science Foundation of China (No. 61403165), the Natural Science Foundation of Jiangsu Province (No. BK20131109), the Post Doctoral Foundation of Jiangsu Province (No. 1501015A), and the Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province (No. 2014SJD381).

Jing Chen received his B.Sc. degree from the School of Mathematical Science and M.Sc. degree from the School of Information Engineering from Yangzhou University (Yanghzou, China) in 2003 and 2006, respectively, and received his Ph.D. degree from the School of Internet of Things Engineering, Jiangnan University (Wuxi, China) in 2013. He is currently a Visiting Professor in the Department of Chemical and Materials Engineering, University of Alberta (Edmonton, Canada). His research interests include Processing Control and system identification.

Bin Jiang received his Ph.D. degree in Automatic Control from Northeastern University (Shenyang, China) in 1995. He had ever been postdoctoral fellow, research fellow, invited professor and visiting professor in Singapore, France, USA and Canada, respectively. Now he is a Chair Professor of Cheung Kong Scholar Program in Ministry of Education and Dean of College of Automation Engineering in Nanjing University of Aeronautics and Astronautics (Nanjing, China). He currently serves as Associate Editor or Editorial Board Member for a number of journals such as IEEE Trans. on Control Systems Technology; IEEE Trans. on Fuzzy Systems; Int. J. of Control, Automation and Systems; Nonlinear Analysis: Hybrid Systems, etc. He is a senior member of IEEE, Chair of Control Systems Chapter in IEEE Nanjing Section, a member of IFAC Technical Committee on Fault Detection, Supervision, and Safety of Technical Processes. His research interests include intelligent fault diagnosis and fault tolerant control and their applications.

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Chen, J., Jiang, B. Modified stochastic gradient parameter estimation algorithms for a nonlinear two-variable difference system. Int. J. Control Autom. Syst. 14, 1493–1500 (2016). https://doi.org/10.1007/s12555-015-0185-x

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  • DOI: https://doi.org/10.1007/s12555-015-0185-x

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