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A rule-based neural controller for inverted pendulum system

J Hao1, J Vandewalle, S Tan

  • 1ESAT Laboratory, Department of Electrical Engineering, Katholieke Universiteit Leuven, Heverlee, Belgium.

International Journal of Neural Systems
|March 1, 1993
PubMed
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This study presents a heuristic neural control method for complex nonlinear problems, successfully swinging up a pendulum on a cart. The approach uses task decomposition and human operator insights for effective control.

Area of Science:

  • Robotics and Control Systems
  • Artificial Intelligence
  • Nonlinear Dynamics

Background:

  • Complex nonlinear control problems are challenging for traditional methods.
  • Existing neural control benchmarks like pendulum balancing have limitations.
  • Heuristic approaches offer potential for complex control tasks.

Purpose of the Study:

  • To demonstrate a heuristic neural control approach for a complex nonlinear regulation problem.
  • To solve the challenging task of swinging up a pendulum on a cart to an upright position.
  • To illustrate a method involving task decomposition, rule extraction, and neural network implementation.

Main Methods:

  • Decomposition of the global control task into pendulum positioning and cart positioning subtasks.

Related Experiment Videos

  • Design of three neural subcontrollers: pendulum subcontroller (PSC), cart subcontroller (CSC), and switching subcontroller (SSC).
  • Development of subcontrollers based on rules and guidelines derived from human operator experience.

    • Main Results:

    • Successful simulation of the heuristic neural control approach for the pendulum-cart system.
    • Demonstration of effective control for swinging up the pendulum and managing cart displacement.
    • Validation of the controller's performance through simulation results.

    Conclusions:

    • The heuristic neural control approach, with task decomposition and human-inspired rules, is effective for complex nonlinear control.
    • The proposed modular controller design (PSC, CSC, SSC) successfully addresses the coupled dynamics of the pendulum-cart system.
    • This method provides a viable alternative for tackling challenging control problems in robotics and automation.