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Direct heuristic dynamic programming for nonlinear tracking control with filtered tracking error.

Lei Yang1, Jennie Si, Konstantinos S Tsakalis

  • 1Department of Control Science and Engineering, Zhejiang University, Hangzhou, China. y_lei@zju.edu.cn

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|June 5, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a direct heuristic dynamic programming design for nonlinear tracking control. The method ensures stable tracking performance despite neural network errors and disturbances.

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Area of Science:

  • Control Systems Engineering
  • Artificial Intelligence
  • Nonlinear Dynamics

Background:

  • Nonlinear systems present significant challenges in achieving precise tracking control.
  • Existing control methods may struggle with uncertainties and approximation errors inherent in adaptive systems.

Purpose of the Study:

  • To design and analyze a nonlinear tracking control system using direct heuristic dynamic programming.
  • To ensure the stability and boundedness of the tracking error and system states.

Main Methods:

  • Employed direct heuristic dynamic programming (DHDP) for controller design.
  • Utilized Lyapunov stability theory for rigorous stability analysis of the closed-loop system.
  • Incorporated a filtered tracking error for enhanced performance.

Main Results:

  • Demonstrated uniform ultimate boundedness of the closed-loop tracking error.
  • Proved uniform ultimate boundedness of the neural network weight estimates.
  • Showcased system robustness against neural network approximation errors and bounded disturbances.

Conclusions:

  • The proposed DHDP-based nonlinear tracking controller ensures stable performance.
  • The approach effectively manages approximation errors and external disturbances.
  • Validated theoretical results through stability analysis.