This paper proposes the optimal state-feedback controller design for the tractor active suspension system via the Lévy-flight intensified current search (LFICuS) algorithm. As one of the newest and most efficient metaheuristic optimization search techniques, the LFICuS algorithm is formed from the behavior of the electrical current in the electric networks associated with the random drawn from the Lévy-flight distribution, the adaptive radius (AR) mechanism and the adaptive neighborhood (AN) mechanism. In this paper, the LFICuS algorithm is applied to optimally design the state-feedback controller for the tractor active suspension system to eliminate the transmitted vibrations to the driver’s cabin caused by road roughness. Results obtained by the LFICuS algorithm will be compared with those obtained by the conventional pole-placement method. As results, the LFICuS algorithm can successfully provide the optimal state-feedback controller for the tractor active suspension system. The tractor active suspension system controlled by the state-feedback controller designed by the LFICuS algorithm yields very satisfactory response with smaller oscillation and faster regulating time than that designed by the pole-placement method, significantly.


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    Titel :

    Optimal State-Feedback Controller Design for Tractor Active Suspension System via Lévy-Flight Intensified Current Search Algorithm


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Vasant, Pandian (Herausgeber:in) / Zelinka, Ivan (Herausgeber:in) / Weber, Gerhard-Wilhelm (Herausgeber:in) / Niyomsat, Thitipong (Autor:in) / Romsai, Wattanawong (Autor:in) / Nawikavatan, Auttarat (Autor:in) / Puangdownreong, Deacha (Autor:in)

    Kongress:

    International Conference on Intelligent Computing & Optimization ; 2021 ; Hua Hin, Thailand December 30, 2021 - December 31, 2021



    Erscheinungsdatum :

    01.01.2022


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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