Adaptive Pseudo Inverse Control for a Class of Nonlinear Asymmetric and Saturated Nonlinear Hysteretic Systems

Xiuyu Zhang, Ruijing Jing, Zhiwei Li, Zhi Li, Xinkai Chen, Chun Yi Su

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

This paper aims at eliminating the asymmetric and saturated hysteresis nonlinearities by designing hysteresis pseudo inverse compensator and robust adaptive dynamic surface control (DSC) scheme. The "pseudo inverse"means that an on-line calculation mechanism of approximate control signal is developed by applying a searching method to the designed temporary control signal where the true control signal is included. The main contributions are summarized as: 1) to our best knowledge, it is the first time to compensate the asymmetric and saturated hysteresis by using hysteresis pseudo inverse compensator because the construction of the true saturated-type hysteresis inverse model is very difficult; 2) by designing the saturated-type hysteresis pseudo inverse compensator, the construction of true explicit hysteresis inverse and the identifications of its corresponding unknown parameters are not required when dealing with the saturated-type hysteresis; 3) by combining DSC technique with the tracking error transformed function, the "explosion of complexity"problem in backstepping method is overcome and the prespecified tracking performance is achieved. Analysis of stability and experimental results on the hardware-in-loop platform illustrate the effectiveness of the proposed adaptive pseudo inverse control scheme.

Original languageEnglish
Article number9242331
Pages (from-to)916-928
Number of pages13
JournalIEEE/CAA Journal of Automatica Sinica
Volume8
Issue number4
DOIs
Publication statusPublished - 2021 Apr

Keywords

  • Adaptive dynamic surface control
  • adaptive pseudo inverse control
  • asymmetric and saturated hysteresis
  • robust control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Artificial Intelligence

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