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Compensation for secondary uncertainty in electro-hydraulic servo system by gain adaptive sliding mode variable structure control

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Abstract

Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system, adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employed to identify the primary uncertainty and the mathematic model of the system was turned into an equivalent linear model with terms of secondary uncertainty. At the same time, gain adaptive sliding mode variable structure control(GASMVSC) was employed to synthesize the control effort. The results show that the unrealization problem caused by some system’s immeasurable state variables in traditional fuzzy neural networks(TFNN) taking all state variables as its inputs is overcome. On the other hand, the identification by the ADRFNNs online with high accuracy and the adaptive function of the correction term’s gain in the GASMVSC make the system possess strong robustness and improved steady accuracy, and the chattering phenomenon of the control effort is also suppressed effectively.

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Authors and Affiliations

  1. School of Mechanical and Electrical Engineering, Central South University, Changsha, 410083, China

    You-wang Zhang  (헅폑췺)

  2. School of Information Science and Engineering, Central South University, Changsha, 410083, China

    Wei-hua Gui  (맰컀뮪)

Authors
  1. You-wang Zhang  (헅폑췺)
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  2. Wei-hua Gui  (맰컀뮪)
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Corresponding author

Correspondence to You-wang Zhang  (헅폑췺).

Additional information

Foundation item: Project(60634020) supported by the National Natural Science Foundation of China

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Zhang, Yw., Gui, Wh. Compensation for secondary uncertainty in electro-hydraulic servo system by gain adaptive sliding mode variable structure control. J. Cent. South Univ. Technol. 15, 256–263 (2008). https://doi.org/10.1007/s11771-008-0048-1

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  • DOI: https://doi.org/10.1007/s11771-008-0048-1

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