Controller Application of a Multi-Layer Quantum Neural Network with Qubit Neurons
Abstrak
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.
Topik & Kata Kunci
Penulis (3)
Kazuhiko TAKAHASHI
Motoki KUROKAWA
Masafumi HASHIMOTO
Akses Cepat
- Tahun Terbit
- 2012
- Sumber Database
- DOAJ
- DOI
- 10.1299/jamdsm.6.526
- Akses
- Open Access ✓