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Author:

Li, Ningning (Li, Ningning.) | Song, Su (Song, Su.)

Indexed by:

CPCI-S

Abstract:

It is a critical problem in the neural network adaptive control system to attenuate the influence of external disturbance or unmodeled dynamics and improve the robustness. In this paper, a novel robust adaptive control based on neural network for unknown nonlinear dynamical systems with bounded disturbances or unmodeled dynamics was proposed. It was realized by using adaptive forecasting and the recursive forgetting factor least square method, also the stability of system was guaranteed by a robust controller. The validity of this control strategy was demonstrated via simulation results.

Keyword:

adaptive forecasting neural network model reference adaptive control (NNMRAC) disturbance recursive least square method robustness

Author Community:

  • [ 1 ] [Li, Ningning]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100022, Peoples R China
  • [ 2 ] [Song, Su]Natl Nat Sci Fdn China, Dept Informat Sci, Beijing 100085, Peoples R China

Reprint Author's Address:

  • [Li, Ningning]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100022, Peoples R China

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Related Keywords:

Source :

WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS

Year: 2006

Page: 2388-,

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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