DocumentCode :
128477
Title :
A particle swarm optimization approach for backstepping sliding mode control for flight simulator servo system
Author :
Fei Li ; Jian-bo Hu ; Chao Zhang ; Jieyu Lei ; Wen-hui Zhu
Author_Institution :
Materiel Manage. & Safety, Eng. Coll., Air Force Eng. Univ., Xi´an, China
fYear :
2014
fDate :
9-11 June 2014
Firstpage :
759
Lastpage :
764
Abstract :
In this paper, an optimal global backstepping sliding mode controller, used for tracking the position of flight simulation turntable, is presented. In order to overcome against the parameter uncertainties and nonlinear friction compensation for the tracking position, a global backstepping sliding mode control is designed. The Lyapunov proof shows the closed-loop system in the presence of this controller global asymptotic stability. Then a novel adaptive inertia weight PSO is proposed in order to obtain the optimal parameters of the global backstepping sliding mode controller . the simulation results confirm desirable performance of the particle swarm optimization and the optimal global backstepping sliding mode control.
Keywords :
Lyapunov methods; aerospace simulation; asymptotic stability; closed loop systems; control system synthesis; friction; nonlinear control systems; optimal control; particle swarm optimisation; position control; servomechanisms; variable structure systems; Lyapunov proof; adaptive inertia weight PSO; closed-loop system; controller global asymptotic stability; flight simulation turntable position tracking; flight simulator servo system; nonlinear friction compensation; optimal global backstepping sliding mode controller; parameter uncertainties; particle swarm optimization approach; Aerospace simulation; Backstepping; Friction; Mathematical model; Optimization; Servomotors; Sliding mode control; backstepping sliding mode control; parameters optimization; particle swarm optimization; uncertainties;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-4316-6
Type :
conf
DOI :
10.1109/ICIEA.2014.6931264
Filename :
6931264
Link To Document :
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