Title :
Remarks on an adaptive-type parallel controller using quantum neural network with qubit neurons
Author :
Takahashi, Koichi
Author_Institution :
Inf. Syst. Design, Doshisha Univ., Kyoto, Japan
Abstract :
This paper presents an adaptive-type parallel controller based on a quantum neural network and investigates its characteristics for control systems. A multi-layer quantum neural network that uses qubit neurons as an information processing unit is utilized to design the adaptive-type parallel controller that conducts the training of the quantum neural network as an online process. Computational experiments to control the single-input single-output nonlinear discrete time plant are conducted in order to evaluate the learning performance and capability of the adaptive-type quantum neural parallel controller. The results of the computational experiments confirm both the feasibility and the effectiveness of the adaptive-type quantum neural parallel controller.
Keywords :
adaptive control; control system synthesis; discrete time systems; learning (artificial intelligence); neurocontrollers; nonlinear control systems; adaptive type parallel controller; control systems; information processing unit; learning performance; online process; quantum neural network; qubit neurons; single-input single-output nonlinear discrete time plant; Biological neural networks; Control systems; Cost function; Neurons; Quantum computing; Training; parallel controller; quantum neural network; qubit neuron; servo control;
Conference_Titel :
Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on
Conference_Location :
Kochi
Print_ISBN :
978-1-4673-5117-1
DOI :
10.1109/ISDA.2012.6416652