1. Self-tuning PID controller using quantum neural network with qubit-inspired neurons.
- Author
-
Takahashi, Kazuhiko, Shiotani, Yuka, and Hashimoto, Masafumi
- Subjects
- *
NEURONS , *SELF-tuning controllers , *PID controllers , *ADAPTIVE control systems , *NEURAL circuitry - Abstract
This paper investigates the performance of an adaptive controller using a multi-layer quantum neural network (QNN) comprising qubit-inspired neurons as information processing units. The control system is a self-tuning controller whose control parameters are tuned online by the QNN to track plant output relative to the desired plant output generated by a reference model. A proportional-integral-derivative (PID) controller is utilized as a conventional controller, with its parameters tuned by the QNN. Computational experiments to control a single-input single-output discrete-time non-linear plant are conducted to evaluate the capability and characteristics of the quantum neural self-tuning controller. The experiment results demonstrate the feasibility and effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
- View/download PDF