• DocumentCode
    2773633
  • Title

    Exponential Stabilization for Suspension System of Vehicle Application

  • Author

    Tung, Shen-Lung ; Juang, Yau-Tarng ; Wu, Wei-Ying

  • fYear
    2010
  • fDate
    16-19 May 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this paper, an active suspension system for the exponential decay control of the three-degree-of-freedom (3DOF) twin-shaft vehicle is proposed. A new exponential stabilization criterion of the second-order vector differential equations is derived and the particle swarm optimization (PSO) method is employed for searching the optimal controller parameters. The proposed method guarantees all of states of the vehicle in an optimally exponentially decaying manner. The simulation results show that the vibration characteristics of the vehicle by the proposed active suspension achieve high performance in the control of the vehicle body vibration and provide higher driving safety than the passive and linear quadratic (LQ) active suspensions.
  • Keywords
    differential equations; optimal control; particle swarm optimisation; road safety; road vehicles; search problems; shafts; suspensions (mechanical components); vectors; vibration control; active suspension system; driving safety; exponential decay control; exponential stabilization criterion; optimal controller parameters; particle swarm optimization method; second-order vector differential equations; three-degree-of-freedom twin-shaft vehicle; vehicle application; vehicle body vibration control; Axles; Damping; Optimal control; Particle swarm optimization; Road safety; Road vehicles; Tires; Vehicle driving; Vehicle safety; Vibration control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Technology Conference (VTC 2010-Spring), 2010 IEEE 71st
  • Conference_Location
    Taipei
  • ISSN
    1550-2252
  • Print_ISBN
    978-1-4244-2518-1
  • Electronic_ISBN
    1550-2252
  • Type

    conf

  • DOI
    10.1109/VETECS.2010.5493970
  • Filename
    5493970