A particle swarm optimization approach for backstepping sliding mode control for flight simulator servo system

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.

[1]  Jin-kun Liu,et al.  QFT Robust Control Design for 3-Axis Flight Table Servo System with Large Friction , 2004 .

[2]  C-H Lu,et al.  Backstepping Sliding-Mode Control for a Pneumatic Control System , 2010 .

[3]  Gao Peng Tracking control of flight simulator servo systems based on NDO , 2011 .

[4]  S. G. Ponnambalam,et al.  Obstacle avoidance control of redundant robots using variants of particle swarm optimization , 2012 .

[5]  Wai Keung Wong,et al.  Feedback controlled particle swarm optimization and its application in time-series prediction , 2012, Expert Syst. Appl..

[6]  Jian Xiao,et al.  A novel chaotic particle swarm optimization based fuzzy clustering algorithm , 2012, Neurocomputing.

[7]  Liang Han,et al.  Discrete sliding mode control based on disturbance observer and its application on flight simulator servo system , 2006, 2006 1st International Symposium on Systems and Control in Aerospace and Astronautics.

[8]  Gang Ma,et al.  A novel particle swarm optimization algorithm based on particle migration , 2012, Appl. Math. Comput..

[9]  Dumitru Baleanu,et al.  A novel adaptive controller for two-degree of freedom polar robot with unknown perturbations , 2012 .

[10]  D.S. Bernstein,et al.  On the LuGre model and friction-induced hysteresis , 2006, 2006 American Control Conference.

[11]  Du Ji-yong Cooperative task assignment for multiple UCAV using particle swarm optimization , 2012 .

[12]  Muhammad Khurram Khan,et al.  A hybrid particle swarm optimization algorithm for high-dimensional problems , 2011, Comput. Ind. Eng..

[13]  Zhimei Chen,et al.  Scheme of Sliding Mode Control based on Modified Particle Swarm Optimization , 2009 .

[14]  Jin-kun Liu,et al.  Nominal Model-Based Sliding Mode Control with Backstepping for 3-Axis Flight Table , 2006 .

[15]  Mounir Ayadi,et al.  PID-type fuzzy logic controller tuning based on particle swarm optimization , 2012, Eng. Appl. Artif. Intell..

[16]  Ren Gao-feng A Genetic Algorithm Based Optimal Excitation Control for Wind Power System Using DC Generator , 2008 .

[17]  Zengqiang Chen,et al.  Chaos particle swarm optimization and T-S fuzzy modeling approaches to constrained predictive control , 2012, Expert Syst. Appl..

[18]  Xianpeng Wang,et al.  A discrete particle swarm optimization algorithm with self-adaptive diversity control for the permutation flowshop problem with blocking , 2012, Appl. Soft Comput..

[19]  Cheng-Chi Wang,et al.  Chaos control in AFM system using sliding mode control by backstepping design , 2010 .

[20]  Somyot Kaitwanidvilai,et al.  Robust loop shaping–fuzzy gain scheduling control of a servo-pneumatic system using particle swarm optimization approach , 2011 .

[21]  Xuemei Ren,et al.  A new PSO algorithm with Random C/D Switchings , 2012, Appl. Math. Comput..