Robust adaptive control for near space vehicles based on wavelet neural network

Author

Yali Xue ; Jie Wen ; Yanli Du

Author_Institution

Coll. of Autom. Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China

fYear

2013

fDate

10-13 Nov. 2013

Firstpage

3735

Lastpage

3739

Abstract

In order to improve the adaptive ability and robustness of the system, the wavelet neural network (WNN) single-scaling frame function with robust controller is used to design the controller. The WNN has self-learning and adaptive ability to approximate nonlinear functions. Combined with the trajectory linearization control (TLC) method, the adaptive robust control strategy and the NSV attitude control system are designed. Then simulations are taken to demonstrate the effectiveness.

Keywords

Lyapunov methods; MIMO systems; adaptive control; approximation theory; attitude control; control system synthesis; nonlinear functions; robust control; space vehicles; trajectory control; unsupervised learning; wavelet neural nets; Lyapunov stability theory; MIMO nonlinear system; NSV attitude control system; TLC method; WNN; adaptive ability; near space vehicles; nonlinear functions; robust adaptive control strategy; robust controller; self-learning ability; trajectory linearization control method; wavelet neural network single-scaling frame function; Adaptive systems; Approximation methods; Neural networks; Nonlinear systems; Robustness; Uncertainty; Wavelet transforms; Near Space Vehicle(NSV); Trajectory Linearization Control(TLC); wavelet neural networks (WNN);

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE

Conference_Location

Vienna

ISSN

1553-572X

Type

conf

DOI

10.1109/IECON.2013.6699730

Filename

6699730