Comparative performance of intelligent algorithms for system identification and control

Alamgir Hossain, Ammr Madkour, Keshav Dahal, Hongniang Yu

    Research output: Contribution to journalArticlepeer-review

    8 Citations (Scopus)
    14 Downloads (Pure)


    This paper presents an investigation into the comparative performance of intelligent system identification and control algorithms within the framework of an active vibration control (AVC) system. Evolutionary Genetic algorithms (GAs) and Adaptive Neuro-Fuzzy Inference system (ANFIS) algorithms are used to develop mechanisms of an AVC system, where the controller is designed based on optimal vibration suppression using the plant model. A simulation platform of a flexible beam system in transverse vibration using finite difference (FD) method is considered to demonstrate the capabilities of the AVC system using GAs and ANFIS. MATLAB GA tool box for GAs and Fuzzy Logic tool box for ANFIS function are used to design the AVC system. The system is men implemented, tested and its performance assessed for GAs and ANFIS based algorithms. Finally, a comparative performance of the algorithms in implementing system identification and corresponding AVC system using GAs and ANFIS is presented and discussed through a set of experiments.
    Original languageEnglish
    Pages (from-to)313-330
    JournalJournal of Intelligent Systems
    Issue number4
    Publication statusPublished - 2008


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