Self-tuning control of a nuclear reactor using a Gaussian function neural network
Journal Article
·
· Nuclear Technology
OSTI ID:64637
- Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of). Dept. of Nuclear Engineering
A self-tuning control method is described for a nuclear reactor system that requires only a set of input-output measurements. The use of an artificial neural network in nonlinear model-based adaptive control, both as a plant model and a controller, is investigated. A neural network called a Gaussian function network is used for one-step-ahead predictive control to track the desired plant output. The effectiveness of the controller is demonstrated by the application of the method to the power tracking control of the Korea Multipurpose Research Reactor.
- OSTI ID:
- 64637
- Journal Information:
- Nuclear Technology, Vol. 110, Issue 2; Other Information: PBD: May 1995
- Country of Publication:
- United States
- Language:
- English
Similar Records
Tuning of power system stabilizers using an artificial neural network
Neural network based approach for tuning of SNS feedback and feedforward controllers.
Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems
Journal Article
·
Sun Dec 01 00:00:00 EST 1991
· IEEE Transactions on Energy Conversion (Institute of Electrical and Electronics Engineers); (United States)
·
OSTI ID:64637
Neural network based approach for tuning of SNS feedback and feedforward controllers.
Conference
·
Tue Jan 01 00:00:00 EST 2002
·
OSTI ID:64637
Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems
Journal Article
·
Mon Nov 01 00:00:00 EDT 2021
· IEEE Transactions on Neural Networks and Learning Systems
·
OSTI ID:64637