Volume 30 Issue 6
Nov.  2021
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SUN Xiaohui, WEN Tao, WEN Chenglin, CHENG Xingshuo, WU Yunkai. High-Order Extended Strong Tracking Filter[J]. Chinese Journal of Electronics, 2021, 30(6): 1152-1158. DOI: 10.1049/cje.2021.08.010
Citation: SUN Xiaohui, WEN Tao, WEN Chenglin, CHENG Xingshuo, WU Yunkai. High-Order Extended Strong Tracking Filter[J]. Chinese Journal of Electronics, 2021, 30(6): 1152-1158. DOI: 10.1049/cje.2021.08.010
shu

High-Order Extended Strong Tracking Filter

  • 1. School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China;

  • 2. School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China;

  • 3. School of Automation, Guangdong University of Petrochemical Technology, Maoming 525000, China;

  • 4. School of Mechatronic Engineering and Automation, Foshan University, Foshan 528225, China;

  • 4. School of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang 212003, China

Funds: 

This work is supported by the National Natural Science Foundation of China (No.61933013, No.61806064, No.61703385, No.61703103, No.U1664264) and Science and Technology Project of China Electric Power Research Institute (No.SGHB0000KXJS1800375).

More Information
  • Received Date: December 16, 2020
  • Revised Date: January 12, 2021
  • Available Online: September 22, 2021
  • Published Date: November 04, 2021
    Graphical Abstract
    • Abstract
  • A novel High-order extended Strong tracking filter (H-STF) is proposed for a class of nonlinear systems. All high-order polynomial terms in the state model are regarded as implicit variables; the original state model is equivalently formulated into a pseudo-linear form; the dynamic relationship between each implicit variable and all variables is modeled; original state model is rewritten into an augmented linear model; the nonlinear measurement model can be rewritten into linear form; taking into account the problems of modeling errors and state mutations that may be caused by the introduction of implicit variables, a high-order extended strong tracking filter is designed. Examples are presented to demonstrate the effectiveness of the new algorithm.
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    • References (16)
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