Journal of Advanced Mechanical Design, Systems, and Manufacturing (Jul 2012)

Controller Application of a Multi-Layer Quantum Neural Network with Qubit Neurons

  • Kazuhiko TAKAHASHI,
  • Motoki KUROKAWA,
  • Masafumi HASHIMOTO

DOI
https://doi.org/10.1299/jamdsm.6.526
Journal volume & issue
Vol. 6, no. 4
pp. 526 – 540

Abstract

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This paper investigates a quantum neural network and discusses its application in control systems. A learning-type neural network-based controller that uses a multi-layer quantum neural network having qubit neurons as its information processing unit is proposed. Three learning algorithms; a back-propagation algorithm, a conjugate gradient algorithm and a real-coded genetic algorithm, are investigated to supervise the training of the multi-layer quantum neural network. To evaluate the learning performance and the capability of the quantum neural network-based controller, we conducted computational experiments for controlling a nonlinear discrete-time plant and a nonholonomic system - in this study a two-wheeled robot. The results of computational experiments confirm both the feasibility and the effectiveness of the quantum neural network-based controller and that the real-coded genetic algorithm is suitable for the learning method of the quantum neural network-based controller.

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