Control of an Inverted Pendulum Using the NeuraBase Network Model

  • Robert Hercus
  • Kit-Yee Wong
  • See-Kiong Shee
  • Kim-Fong Ho
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8227)


This paper presents an alternative approach for the control and balancing operations of an inverted pendulum. The proposed method uses a neuronal network called NeuraBase to learn the sensor events obtained via a rotary encoder and the motor events controlling a stepper motor, which rotates the swinging arm. A neuron layer called the controller network will link the sensor neuron events to the motor neurons. The proposed NeuraBase network model (NNM) has demonstrated its ability to successfully control the balancing operation of the pendulum in the absence of a dynamic model and theoretical control methods. The controller also demonstrated its robustness in the adaptive learning of pendulum balancing with imposed system changes.


Adaptive Control Real-time Control Online Control Neural Network Inverted Pendulum Balancing Control 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Robert Hercus
    • 1
  • Kit-Yee Wong
    • 1
  • See-Kiong Shee
    • 1
  • Kim-Fong Ho
    • 1
  1. 1.Neuramatix Sdn BhdKuala LumpurMalaysia

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