Abstract

This paper makes use of the direct heuristic dynamic programming design in a nonlinear tracking control setting with filtered tracking error. A Lyapunov stability approach is used for the stability analysis of the tracking system. It is shown that the closed-loop tracking error and the approximating neural network weight estimates retain the property of uniformly ultimate boundedness under the presence of neural network approximation error and bounded unknown disturbances under certain conditions.

Original languageEnglish (US)
Pages (from-to)1617-1622
Number of pages6
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume39
Issue number6
DOIs
StatePublished - 2009

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Dynamic programming
Neural networks

Keywords

  • Approximate dynamic programming (ADP)
  • Direct heuristic dynamic programming (direct HDP)
  • Lyapunov stability
  • Tracking control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Human-Computer Interaction
  • Information Systems
  • Software

Cite this

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abstract = "This paper makes use of the direct heuristic dynamic programming design in a nonlinear tracking control setting with filtered tracking error. A Lyapunov stability approach is used for the stability analysis of the tracking system. It is shown that the closed-loop tracking error and the approximating neural network weight estimates retain the property of uniformly ultimate boundedness under the presence of neural network approximation error and bounded unknown disturbances under certain conditions.",
keywords = "Approximate dynamic programming (ADP), Direct heuristic dynamic programming (direct HDP), Lyapunov stability, Tracking control",
author = "Lei Yang and Jennie Si and Konstantinos Tsakalis and Armando Rodriguez",
year = "2009",
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AU - Tsakalis, Konstantinos

AU - Rodriguez, Armando

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AB - This paper makes use of the direct heuristic dynamic programming design in a nonlinear tracking control setting with filtered tracking error. A Lyapunov stability approach is used for the stability analysis of the tracking system. It is shown that the closed-loop tracking error and the approximating neural network weight estimates retain the property of uniformly ultimate boundedness under the presence of neural network approximation error and bounded unknown disturbances under certain conditions.

KW - Approximate dynamic programming (ADP)

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KW - Tracking control

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