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Original scientific paper

Adaptive Neural Network Controller for Thermogenerator Angular Velocity Stabilization System

Krunoslav Horvat ; Brodarski Institute, Zagreb
Ines Šoić ; Brodarski Institute, Zagreb
Ognjen Kuljača ; Brodarski Institute, Zagreb

Fulltext: english, pdf (676 KB) pages 0-0 downloads: 336* cite
APA 6th Edition
Horvat, K., Šoić, I. & Kuljača, O. (2013). Adaptive Neural Network Controller for Thermogenerator Angular Velocity Stabilization System. Brodogradnja, 64 (2), 0-0. Retrieved from https://hrcak.srce.hr/104494
MLA 8th Edition
Horvat, Krunoslav, et al. "Adaptive Neural Network Controller for Thermogenerator Angular Velocity Stabilization System." Brodogradnja, vol. 64, no. 2, 2013, pp. 0-0. https://hrcak.srce.hr/104494. Accessed 29 Nov. 2021.
Chicago 17th Edition
Horvat, Krunoslav, Ines Šoić and Ognjen Kuljača. "Adaptive Neural Network Controller for Thermogenerator Angular Velocity Stabilization System." Brodogradnja 64, no. 2 (2013): 0-0. https://hrcak.srce.hr/104494
Harvard
Horvat, K., Šoić, I., and Kuljača, O. (2013). 'Adaptive Neural Network Controller for Thermogenerator Angular Velocity Stabilization System', Brodogradnja, 64(2), pp. 0-0. Available at: https://hrcak.srce.hr/104494 (Accessed 29 November 2021)
Vancouver
Horvat K, Šoić I, Kuljača O. Adaptive Neural Network Controller for Thermogenerator Angular Velocity Stabilization System. Brodogradnja [Internet]. 2013 [cited 2021 November 29];64(2):0-0. Available from: https://hrcak.srce.hr/104494
IEEE
K. Horvat, I. Šoić and O. Kuljača, "Adaptive Neural Network Controller for Thermogenerator Angular Velocity Stabilization System", Brodogradnja, vol.64, no. 2, pp. 0-0, 2013. [Online]. Available: https://hrcak.srce.hr/104494. [Accessed: 29 November 2021]

Abstracts
The paper presents an analytical and simulation approach for the selection of activation functions for the class of neural network controllers for ship’s thermogenerator angular velocity stabilization system. Such systems can be found in many ships. A Lyapunov-like stability analysis is performed in order to obtain a weight update law. A number of simulations were performed to find the best activation function using integral error criteria and statistical T-tests.

Keywords
activation function; adaptive neural network; tracking problem

Hrčak ID: 104494

URI
https://hrcak.srce.hr/104494

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