DocumentCode
1691982
Title
Neural backstepping control: Green energy applications
Author
Ruiz, R. ; Sanchez, E.N. ; Loukianov, A.G.
fYear
2012
Firstpage
1
Lastpage
4
Abstract
In this paper, the authors present a discrete-time adaptive neural backstepping control for a doubly fed induction generator (DFIG), based on a discrete-time high order neural network (HONN), which is trained with a new particle swarm optimization extended Kalman filter (PSOEKF) algorithm. The discrete-time adaptive neural backstepping control performance is illustrated via simulations.
Keywords
Kalman filters; adaptive control; asynchronous generators; discrete time systems; neurocontrollers; particle swarm optimisation; adaptive neural backstepping control; discrete time control; doubly fed induction generator; extended Kalman filter; green energy application; high order neural network; particle swarm optimization; Backstepping; Induction generators; Kalman filters; Particle swarm optimization; Rotors; Stators; Torque; Doubly Fed Induction Generator; Grid Side Converter; Inverse Optimal Control; Particle Swarm Optimization; Rotor Side Converter; Wind Energy;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems (LASCAS), 2012 IEEE Third Latin American Symposium on
Conference_Location
Playa del Carmen
Print_ISBN
978-1-4673-1207-3
Type
conf
DOI
10.1109/LASCAS.2012.6180328
Filename
6180328
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