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Gradient-based Iterative Parameter Estimation for a Finite Impulse Response System with Saturation Nonlinearity

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  • Control Theory and Applications
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Abstract

This paper studies the identification problems of a nonlinear finite impulse response system with saturation nonlinearity. Introducing a symbolic function, an over-parameterization gradient-based iterative algorithm is presented for estimating the parameters of the nonlinear system with saturation nonlinearity. In order to enhance the computational efficiency, a gradient-based iterative algorithm and a hierarchical gradient-based iterative algorithm are presented for the nonlinear systems. The computational loads of these algorithms are analyzed and compared.

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Authors and Affiliations

  1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), the School of Internet of Things Engineering, Jiangnan University, Wuxi, 214122, China

    Xiao Wang, Cheng Wang & Feng Ding

  2. Science and Technology on Near-Surface Detection Laboratory, Wuxi, 214028, China

    Yingjiao Rong & Cheng Wang

  3. Department of Mathematics, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Tasawar Hayat

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  1. Xiao Wang
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  2. Yingjiao Rong
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  3. Cheng Wang
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  4. Feng Ding
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Correspondence to Cheng Wang.

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Recommended by Associate Editor Le Van Hien under the direction of Editor Jay H. Lee. This work was supported by the National Natural Science Foundation of China (No. 61803049), Natural Science Fundamental Research Project of Colleges and Universities in Jiangsu Province (Nos. 17KJB120001 and 20KJB120006), the Key Program Special Fund in XJTLU (No. KSF-E-12), the Science and Technology on Near-Surface Detection Laboratory (No. 6142414180104) and the 111 Project (B12018).

Xiao Wang was born in Suqian, Jiangsu Province, China in 1997. He received his B.Sc. degree from Nanjing Forestry University, Nanjing, China in 2019. He is currently a Master’s student in the School of Internet of Things Engineering, Jiangnan University, Wuxi, China. His interests include system modeling, system identification and parameter estimation.

Yingjiao Rong received her B.Sc. degree from the Department of Automatic Control, Nanjing University of Science and Technology (Nanjing, China) in 2000 and received her M.Sc. degree from the School of Internet of Things Engineering, Jiangnan University, Wuxi, China in 2013. Currently, she is an engineer of the Science and Technology on Near Surface Detection Laboratory since 2000. Her research interests include intelligent detection and intelligent tracking.

Cheng Wang received his Ph.D. degree in transportation information engineering and control from Beijing Jiaotong University in 2014. He has been an associate professor at the School of Internet of Things Engineering, Jiangnan University since 2019. His research interest covers modeling and control of nonlinear systems, advanced train control methods, machine learning and data mining.

Feng Ding received his B.Sc. degree from the Hubei University of Technology, Wuhan, China in 1984, and his M.Sc. and Ph.D. degrees both from the Tsinghua University, in 1991 and 1994, respectively. He has been a professor in the School of Internet of Things Engineering at the Jiangnan University (Wuxi, China) since 2004. His current research interests include model identification and adaptive control. He authored five books on System Identification.

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Wang, X., Rong, Y., Wang, C. et al. Gradient-based Iterative Parameter Estimation for a Finite Impulse Response System with Saturation Nonlinearity. Int. J. Control Autom. Syst. 20, 73–83 (2022). https://doi.org/10.1007/s12555-020-0872-0

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