University Library
  • Login
A gateway to Melbourne's research publications
Minerva Access is the University's Institutional Repository. It aims to collect, preserve, and showcase the intellectual output of staff and students of the University of Melbourne for a global audience.
View Item 
  • Minerva Access
  • Engineering and Information Technology
  • Mechanical Engineering
  • Mechanical Engineering - Research Publications
  • View Item
  • Minerva Access
  • Engineering and Information Technology
  • Mechanical Engineering
  • Mechanical Engineering - Research Publications
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

    Performance Analysis of a Semiactive Suspension System with Particle Swarm Optimization and Fuzzy Logic Control

    Thumbnail
    Download
    Published version (1.477Mb)

    Citations
    Scopus
    Altmetric
    12
    Author
    Qazi, AJ; de Silva, CW; Khan, A; Khan, MT
    Date
    2014-01-01
    Source Title
    The Scientific World Journal
    Publisher
    HINDAWI LTD
    University of Melbourne Author/s
    DE SILVA, CLARENCE
    Affiliation
    Mechanical Engineering
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Qazi, A. J., de Silva, C. W., Khan, A. & Khan, M. T. (2014). Performance Analysis of a Semiactive Suspension System with Particle Swarm Optimization and Fuzzy Logic Control. SCIENTIFIC WORLD JOURNAL, 2014, https://doi.org/10.1155/2014/174102.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/262807
    DOI
    10.1155/2014/174102
    Abstract
    This paper uses a quarter model of an automobile having passive and semiactive suspension systems to develop a scheme for an optimal suspension controller. Semi-active suspension is preferred over passive and active suspensions with regard to optimum performance within the constraints of weight and operational cost. A fuzzy logic controller is incorporated into the semi-active suspension system. It is able to handle nonlinearities through the use of heuristic rules. Particle swarm optimization (PSO) is applied to determine the optimal gain parameters for the fuzzy logic controller, while maintaining within the normalized ranges of the controller inputs and output. The performance of resulting optimized system is compared with different systems that use various control algorithms, including a conventional passive system, choice options of feedback signals, and damping coefficient limits. Also, the optimized semi-active suspension system is evaluated for its performance in relation to variation in payload. Furthermore, the systems are compared with respect to the attributes of road handling and ride comfort. In all the simulation studies it is found that the optimized fuzzy logic controller surpasses the other types of control.

    Export Reference in RIS Format     

    Endnote

    • Click on "Export Reference in RIS Format" and choose "open with... Endnote".

    Refworks

    • Click on "Export Reference in RIS Format". Login to Refworks, go to References => Import References


    Collections
    • Minerva Elements Records [53039]
    • Mechanical Engineering - Research Publications [388]
    Minerva AccessDepositing Your Work (for University of Melbourne Staff and Students)NewsFAQs

    BrowseCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
    My AccountLoginRegister
    StatisticsMost Popular ItemsStatistics by CountryMost Popular Authors