Optimization of the exponential stabilization problem in active suspension system using PSO

Shen Lung Tung, Yau Tarng Juang, Wei Hsun Lee, Wern Yarng Shieh, Wei Ying Wu

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

This paper proposes an active suspension mechanism for three-degree-of- freedom (3-DOF) twin-shaft vehicles of front axle suspension with bounded uncertainties using exponential decay control and particle swarm optimization (PSO) techniques. A new exponential stabilization criterion of the system via the dynamic state feedback control is derived and the optimization problem of exponential stabilization is discussed. The optimization problem is solved by using PSO method to guarantee all the states of vehicles in an optimal exponential decay in nearly real-time. Simulation results in both frequency and time domains show that the vibration characteristics of vehicles for the proposed active suspension system achieve significant improvements over the passive and linear quadratic (LQ) active suspension systems.

Original languageEnglish
Pages (from-to)14044-14051
Number of pages8
JournalExpert Systems With Applications
Volume38
Issue number11
DOIs
Publication statusPublished - 2011 Oct 1

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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