Pregled bibliografske jedinice broj: 438527
Adaptive Two Layer Neural Network Frequency Controller for Isolated Thermal Power System
Adaptive Two Layer Neural Network Frequency Controller for Isolated Thermal Power System // Engineering/Computing and Systems Research E-Conference CISSE 2009, International Conference on Industrial Electronics, Technology & Automation IETA 09 / NA (ur.).
Bridgeport (CT), 2009. str. CD-CD (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 438527 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Adaptive Two Layer Neural Network Frequency Controller for Isolated Thermal Power System
Autori
Kuljaca, Ognjen ; Horvat, Krunoslav ; Gadewadikar, Jyotirmay
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Engineering/Computing and Systems Research E-Conference CISSE 2009, International Conference on Industrial Electronics, Technology & Automation IETA 09
/ NA - Bridgeport (CT), 2009, CD-CD
Skup
International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 09) - International Conference on Industrial Electronics, Technology & Automation (IETA 09)
Mjesto i datum
NA, 4-12.12.2209
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Adaptive Neural Network; Frequency Controller; Isolated Thermal Power System
Sažetak
An adaptive neural network control scheme for thermal power system is described. Neural network control scheme presented in this paper does not require off-line training. The online tuning algorithm and neural network architecture are described. The performance of the controller is illustrated via simulation for different changes in process parameters and for different disturbances. Performance of neural network controller is compared with conventional proportional-integral control scheme for frequency control in thermal power systems. Neural network control scheme described here is not linear-in-parameter. Neural network has two layers and nodes weights in both layers are tuned.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
192-0361557-1564 - Inteligentno upravljanje hidroenergetskim postrojenjima
Ustanove:
Brodarski institut d.o.o.