A neural network based alternator power angle estimation method for marine electrical network supervision and control
Résumé
A neural network based alternator power angle estimation method is presented in this paper. The method is dedicated to detect load commutations in marine electrical network and to issue scheduling variables to gain scheduling controller. The global objective is to deal with the unexpected parameter oscillations problem in transient process when load commutations happen.
Mots clés
alternators
commutation
marine systems
neurocontrollers
power generation control
power generation scheduling
alternator power angle estimation method
gain scheduling controller
load commutation detection
marine electrical network supervision-and-control
marine power generation
transient process
Control systems
Electric variables control
Neural networks
Power system transients
Propulsion
Scheduling
Switches
Three-term control
Electrical machine
Embarked networks
Estimation technique
Neural network