Title :
Robust adaptive neural network control of aircraft braking system
Author :
Bihua Chen ; Zongxia Jiao ; Shuzhi Sam Ge ; Chengwen Wang
Author_Institution :
Sci. & Technol. on Aircraft Control Lab., Beihang Univ., Beijing, China
Abstract :
This paper addresses the nonlinear robust braking control of aircraft. We consider the unknown aerodynamic forces and moments which will degrade the brake performance significantly. Moreover, for the transport or commercial air-crafts, weight variation will influence the braking control torque calculation. In this paper, robust adaptive control is proposed for aircraft braking system. By integrating a neural network (NN) estimator to approximate unknown aerodynamic forces and moments, the proposed control can effectively suppress the aerodynamic uncertainties and weight variation. The brake torque input constraint is also discussed in this paper. Simulation results clearly demonstrate the advantages and effectiveness of the proposed method.
Keywords :
adaptive control; aerodynamics; aircraft control; brakes; braking; force control; neurocontrollers; nonlinear control systems; robust control; torque control; uncertain systems; vehicle dynamics; aerodynamic uncertainty suppression; aircraft braking system; braking control torque calculation; neural network estimator; nonlinear robust braking control; robust adaptive neural network control; unknown aerodynamic forces; unknown aerodynamic moments; weight variation; Aerodynamics; Aerospace control; Aircraft; Force; Friction; Gears; Wheels;
Conference_Titel :
Industrial Informatics (INDIN), 2012 10th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-0312-5
DOI :
10.1109/INDIN.2012.6301235