DocumentCode :
1603015
Title :
The experimental study of neural network control system for a micro turbine engine
Author :
Zhang, Tian-Hong ; Huang, Xianghua ; Li, Qiu-Hua
Author_Institution :
Coll. of Energy & Power Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
fYear :
2009
Firstpage :
1264
Lastpage :
1267
Abstract :
In order to deal with the control problems of nonlinearity and difficulty of establishing an exact model of a micro turbine engine, a control algorithm based on neural network is proposed. The RBF neural network can identify the output value online, which is used by the single neuron controller to adjust its parameters based on a gradient algorithm. The simulation and rig test experiments show that, the neural network control algorithm has good real-time characteristic, tracking ability and robustness in the whole working range of 125000 r/min with the over shoot of less than 500 r/min and the stable error of less than 200r/min, which can meet the demands of micro turbine engine state regulation.
Keywords :
aerospace engines; neurocontrollers; nonlinear control systems; radial basis function networks; regulation; robust control; tracking; turbines; RBF neural network; aerospace engine; gradient algorithm; micro turbine engine; neural network control system; nonlinearity control; robust control; state regulation; tracking ability; Control systems; Convergence; Engines; Neural networks; Neurons; Optimal control; Real time systems; Robust control; Smoothing methods; Turbines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Asian Control Conference, 2009. ASCC 2009. 7th
Conference_Location :
Hong Kong
Print_ISBN :
978-89-956056-2-2
Electronic_ISBN :
978-89-956056-9-1
Type :
conf
Filename :
5276258
Link To Document :
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