Addressing to the difficulties in PID parameter tuning, low accuracy in temperature controlling and the dissatisfaction in high exactitude extrusion processing of the present PID controllers, a new kind of PID controller based on RBF neural network is proposed. It can not only obtain a higher accuracy in temperature controlling, but also infinitely approach the nonlinear system with quicker and more stable convergence by fuzzy variable step sizes in the adaptive optimizations. The simulation results show that the proposed PID controller shortens the transient response time obviously with good system stability. It has a better performance in the barrel temperature controlling than other traditional PID controllers.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Fuzzy Barrel Temperature PID Controller Based on Neural Network


    Beteiligte:
    Jiang, Jing (Autor:in) / Wen, Shengping (Autor:in) / Zhou, Zhiheng (Autor:in) / He, Hezhi (Autor:in)


    Erscheinungsdatum :

    01.05.2008


    Format / Umfang :

    392259 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Neural Network Tuned Fuzzy Controller for MIMO System

    Seema Chopra / R. Mitra / Vijay Kumar | BASE | 2007

    Freier Zugriff

    Autotuning of Fuzzy Logic Controller using Neural Network

    Van Cleave, D. W. / IEEE | British Library Conference Proceedings | 2000


    Tuning of fuzzy logic controller using neural network

    van Cleave, D. / Rattan, K.S. | IEEE | 2000


    An Optimal Fuzzy Neural Network Controller Based on Artificial Immune Principle

    Zuo, X.-q. / Li, S.-y. | British Library Online Contents | 2004


    PID ramp controller regulated by fuzzy RBF neural network

    Jiang, Tao / Liang, Xinrong | Tema Archiv | 2009