Backstepping control strategy for aero-engine using neural networks

PAN Mu-xuan; HUANG Jin-quan; YIN Shi

Volume 24 Issue 10

Oct. 2009

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PAN Mu-xuan, HUANG Jin-quan, YIN Shi. Backstepping control strategy for aero-engine using neural networks[J]. Journal of Aerospace Power, 2009, 24(10): 2344-2348.

Citation:

PAN Mu-xuan, HUANG Jin-quan, YIN Shi. Backstepping control strategy for aero-engine using neural networks[J]. Journal of Aerospace Power, 2009, 24(10): 2344-2348.

PAN Mu-xuan, HUANG Jin-quan, YIN Shi. Backstepping control strategy for aero-engine using neural networks[J]. Journal of Aerospace Power, 2009, 24(10): 2344-2348.

Citation:

PAN Mu-xuan, HUANG Jin-quan, YIN Shi. Backstepping control strategy for aero-engine using neural networks[J]. Journal of Aerospace Power, 2009, 24(10): 2344-2348.

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Backstepping control strategy for aero-engine using neural networks

College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Received Date: 2008-10-09
Rev Recd Date: 2009-03-24
Publish Date: 2009-10-28

Abstract

Abstract

A Backstepping control strategy based on neural network was presented in view of nonlinearity and uncertainty of aero-engine.Radial basis function(RBF) neural network was used to estimate the equations of the unknown system,and a smooth-switching algorithm was proposed to avoid singularity phenomenon.Using Lyapunov stability analysis,the uniformly ultimately boundedness of closed-loop systems was proven.Finally,the compressor speed controller was designed based on a nonlinear model of some turbofan engine.The simulation results illustrate the effectiveness of the proposed approach.
- aero-engine,
- nonlinear system,
- neural network,
- backstepping control