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Helicopter trimming and tracking control using direct neural dynamic programming.

R Enns1, Jennie Si

  • 1Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ, USA.

IEEE Transactions on Neural Networks
|February 2, 2008
PubMed
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This study introduces a neural-network control system for complex tasks like helicopter flight. The direct neural dynamic programming (DNDP) method enables learning helicopter maneuvers and general tracking control.

Area of Science:

  • Aerospace Engineering
  • Control Theory
  • Artificial Intelligence

Background:

  • Complex control problems, such as helicopter flight control, require advanced methodologies.
  • Existing control systems may struggle with nonlinear dynamics and uncertainties inherent in such systems.

Purpose of the Study:

  • To develop and evaluate a neural-network-based approximate dynamic programming control mechanism for complex systems.
  • To tailor the direct neural dynamic programming (DNDP) framework for helicopter flight control design and maneuver learning.
  • To assess the robustness and applicability of the DNDP approach on a realistic helicopter model.

Main Methods:

  • Implementation of a direct neural dynamic programming (DNDP) control framework.
  • Integration of a trim network within the neural dynamic programming (NDP) controller for nonlinear system control.

Related Experiment Videos

  • Extensive simulation studies using the FLYRT nonlinear validated model of an Apache helicopter.
  • Evaluation of control system performance under various disturbance conditions to ensure design robustness.

    • Main Results:

    • Successful application of the DNDP methodology to a complex, continuous state, multiple-input multiple-output nonlinear system (Apache helicopter).
    • Demonstration of the control system's ability to learn helicopter maneuvers and perform tracking control.
    • Validation of design robustness through simulations under diverse disturbance scenarios.
    • The DNDP control system framework proved effective for the Apache helicopter model.

    Conclusions:

    • The DNDP-based control system offers a viable solution for complex nonlinear control problems, exemplified by helicopter flight control.
    • This systematic application of approximate dynamic programming to a complex, uncertain system represents a significant advancement.
    • The developed DNDP framework is adaptable and shows potential for general-purpose tracking control applications beyond helicopters.