Robust control research on adaptive wavelet neural network identification for tank all-electric gun control system

Author

Hong-Yan, Wang ; Ji-Hong, Qiao

Author_Institution

Dept. of Inf. Eng., Acad. of Armored Force Eng., Beijing, China

Volume

1

fYear

2011

Firstpage

375

Lastpage

379

Abstract

Complex plants seldom fulfill the conditions required for the direct feedback linearization(DFL) control. Aiming at the mathematic model not known exactly, wavelet neural network(WNN) identifier combined with H_∞ controller is proposed. WNN is used to approximate the unknown function, novel control and update laws for the weights in the WNN are derived to guarantee that the tracking error is uniformly ultimately bounded (UUB) in the sense of Lyapunov. In addition, a variable structure control and H_∞ robust compensator is designed to improve the tracking performance. This control method is used to the AC all-electrical tank gun control system, computer simulations show that the tracking accuracy is much better and the control system has strong adaptability and robustness.

Keywords

H^∞ control; Lyapunov methods; feedback; linearisation techniques; military systems; neurocontrollers; radial basis function networks; robust control; variable structure systems; weapons; AC all electrical tank gun control system; H_∞ controller; H_∞ robust compensator; Lyapunov method; adaptive wavelet neural network identification; direct feedback linearization control; mathematic model; robust control research; variable structure control; wavelet neural network; Adaptation models; Adaptive systems; Asymptotic stability; Control systems; Mathematical model; Robustness; Stability analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Information Processing (ICICIP), 2011 2nd International Conference on

Print_ISBN

978-1-4577-0813-8

Type

conf

DOI

10.1109/ICICIP.2011.6008268

Filename

6008268