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An Examination of Qubit Neural Network in Controlling an Inverted Pendulum

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Abstract

The Qubit neuron model is a new non-standard computing scheme that has been found by simulations to have efficient processing abilities. In this paper we investigate the usefulness of the model for a non linear kinetic control application of an inverted pendulum on a cart. Simulations show that a neural network based on Qubit neurons would swing up and stabilize the pendulum, yet it also requires a shorter range over which the cart moves as compared to a conventional neural network model.

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Abbreviations

CNN:

conventional neural network

QBP:

quantum back propagation

QNN:

qubit neural network

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Authors and Affiliations

  1. Matsue National College of Technology, Japan

    Noriaki kouda

  2. Division of Computer Engineering, Graduate School of Engineering, Himeji Institute of Technology, University of Hyogo, Japan

    Nobuyuki Matsui

  3. Graduate School of Applied Informatics, University of Hyogo, Japan

    Haruhiko Nishimura

  4. National Institute of Information and Communications Technology, Japan

    Ferdinand Peper

Authors
  1. Noriaki kouda
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  2. Nobuyuki Matsui
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  3. Haruhiko Nishimura
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  4. Ferdinand Peper
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Corresponding author

Correspondence to Noriaki kouda.

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kouda, N., Matsui, N., Nishimura, H. et al. An Examination of Qubit Neural Network in Controlling an Inverted Pendulum. Neural Process Lett 22, 277–290 (2005). https://doi.org/10.1007/s11063-005-8337-2

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  • DOI: https://doi.org/10.1007/s11063-005-8337-2

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