Browse > Article
http://dx.doi.org/10.12673/jant.2014.18.2.107

Turbojet Engine Control of UAV using Artificial Neural Network PID  

Kim, Dae-Gi (Avionics Engineering, HanSeo University)
Hong, Gyo-Young (Avionics Engineering, HanSeo University)
Ahn, Dong-Man (Avionics Engineering, HanSeo University)
Hong, Seung-Beom (Avionics Engineering, HanSeo University)
Jie, Min-Seok (Avionics Engineering, HanSeo University)
Publication Information
Journal of Advanced Navigation Technology / v.18, no.2, 2014 , pp. 107-113 More about this Journal
Abstract
In this paper, controller Propose to prevent compressor surge and improve the transient response of the fuel flow control system of turbojet engine. Turbojet engine controller is designed by applying Artificial Neural Network PID control algorithm and make an inference by applying Artificial Neural Network Error Back Propagation Algorithm. To prevent any surge or a flame out event during the engine acceleration or deceleration, the ANN PID controller effectively controls the fuel flow input of the control system. ANN PID results are used as the fuel flow control inputs to prevent compressor surge and flame-out for turbo-jet engine and the controller is designed to converge to the desired speed quickly and safely. Using MATLAB to perform computer simulations verified the performance of the proposed controller. Response characteristics pursuant to the gain were analyzed by simulation.
Keywords
Turbojet engine; Artificial Neural Network PID controller; Surge control; Fuel flow control;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 M. Montazeri-Gh, H. Yousefpour and S. Jafari, "Fuzzy logic computing for design of gas turbine engine fuel control system," in Computer and Automation Engineering (ICCAE), Singapore, Vol.5, pp. 723-727, 2010.
2 H. Y. Cao and F. M. Peng, "Optimization of engine speed neural network PID controller based on genetic algorithm," in Computational Intelligence and Design(ISCID), Hangzhou: China, Vol.2, pp. 271-274, 2011.
3 M. Jing, "Adaptive control of the aircraft turbojet engine based on the neural network," in International Conference. Computational Intelligence and Security, Guangzhou: China, Vol. 1, pp. 937-940, 2006.
4 H. Badihi, A. Shahriari and A. Naghsh, "Artificial neural network application to fuel flow function for demanded jet engine performance," in IEEE Aerospace Conference, Big Sky: MT, pp 1-7. 2009.
5 X. Yao, "Evolving artificial neural networks," Proceedings of The IEEE, Vol 87, No.9, pp. 1423-1447, Sep. 1999.
6 I. S. Oh, Pattern Recognition, Seoul, Korea: Kyobobook, 2012.
7 L. Xu, "General fuzzy neural network: theory and applications," in IEEE International Conference on Fuzzy Systems, Seoul: Korea, Vol. 3, pp. 1649-1654, 1999.
8 J. Y. Lee and J. S. Lim "Artificial neural network approach to selection of enhanced oil recovery method," The Korean Society of Mineral and Energy Resources Engineers, Vol. 45, No. 6, pp. 719-726, 2008.   과학기술학회마을