A Method of Hybrid Neural Network Adaptive Control for Flight Control System

Author

Wei, Gu ; Dan, Li ; Weiguo, Zhang ; Xiaoxiong, Liu

Author_Institution

Coll. of Autom., Northwestern Polytech. Univ., Xian, China

Volume

1

fYear

2010

fDate

11-12 May 2010

Firstpage

160

Lastpage

163

Abstract

It is difficult to establish accurate models for complex flight control systems, but neural network has arbitrary nonlinear approximation ability. In order to overcome modeling errors and disturbances, a method of hybrid flight control is proposed. Firstly, inverse model of the object is identified online through neural networks and the feedback linearization control system is reached. And then circle theorem is used to design linear robust controller to control the state variables follow the input. A dynamic longitudinal model of a high-performance aircraft is considered to demonstrate the effectiveness of the proposed control scheme. Simulation results show designed controllers are highly adaptive and anti-interference ability.

Keywords

adaptive control; aerospace control; aircraft; feedback; neurocontrollers; robust control; feedback linearization control system; flight control system; high performance aircraft; hybrid neural network adaptive control; linear robust controller; nonlinear approximation ability; Adaptive control; Aerospace control; Aircraft; Control system synthesis; Error correction; Inverse problems; Linear feedback control systems; Neural networks; Neurofeedback; Robust control; Flight control; PID control; adaptive inverse control; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on

Conference_Location

Changsha

Print_ISBN

978-1-4244-7279-6

Electronic_ISBN

978-1-4244-7280-2

Type

conf

DOI

10.1109/ICICTA.2010.666

Filename

5523522