Adaptive-type servo controller utilizing a quantum neural network with qubit neurons

Article type: Research Article

Authors: Takahashi, Kazuhiko

Affiliations: Information Systems Design, Faculty of Science and Engineering, Doshisha University, Kyoto, Japan. E-mail: [email protected]

Abstract: This study presents an adaptive-type controller based on a quantum neural network and investigates its characteristics for control systems. A multi-layer quantum neural network which uses qubit neurons as an information processing unit is utilized to design three types of the adaptive-type quantum-neural-network-based controllers which conduct the learning of the quantum neural network as an online process: a direct controller, a parallel controller and an indirect controller. Computational experiments to control the single-input single-output non-linear discrete-time plant are conducted to evaluate the learning performance and capability of quantum neural controllers. The results of the computational experiments confirm the feasibility and effectiveness of adaptive-type quantum neural controllers.

Keywords: Quantum neural network, qubit neuron, servo control, direct controller, parallel controller, indirect controller

DOI: 10.3233/HIS-130174

Journal: International Journal of Hybrid Intelligent Systems, vol. 10, no. 3, pp. 151-164, 2013