Self-teaching neural network learns difficult reactor control problem

Conference · Sat Dec 31 23:00:00 EST 1988 · Transactions of the American Nuclear Society; (USA)

OSTI ID:6769081

Jouse, W C

A self-teaching neural network used as an adaptive controller quickly learns to control an unstable reactor configuration. The network models the behavior of a human operator. It is trained by allowing it to operate the reactivity control impulsively. It is punished whenever either the power or fuel temperature stray outside technical limits. Using a simple paradigm, the network constructs an internal representation of the punishment and of the reactor system. The reactor is constrained to small power orbits.

• OSTI ID: 6769081
• Report Number(s): CONF-891103--
• Journal Information: Transactions of the American Nuclear Society; (USA), Journal Name: Transactions of the American Nuclear Society; (USA) Vol. 60; ISSN TANSA; ISSN 0003-018X
• Country of Publication: United States
• Language: English

Related Subjects

22 GENERAL STUDIES OF NUCLEAR REACTORS
220400* -- Nuclear Reactor Technology-- Control Systems
ARTIFICIAL INTELLIGENCE
CONTROL SYSTEMS
HUMAN FACTORS
NEURAL NETWORKS
NUCLEAR FACILITIES
NUCLEAR POWER PLANTS
OPERATION
PERSONNEL
POWER PLANTS
REACTOR CONTROL SYSTEMS
REACTOR OPERATION
REACTOR OPERATORS
THERMAL POWER PLANTS
TRAINING