In this paper, a novel approach is presented for optimization of sliding mode controller parameters. The main purpose is to optimize sliding surface slope and thickness of the boundary layer. The tuning of the electrical drive controller is a complex problem due to the many non-linearities of the machines, power converter and controller. Therefore, it is difficult to develop mathematical models of the system accurately because of unknown and unavoidable parameter variations due to saturation temperature variations and system disturbance. To solve that problem artificial neural network (ANN) is used. That is, the whole system is modeled by using ANN. Then, sliding surface slope and thickness of the boundary layer is optimized using genetic algorithms. The proposed method is applied to an induction motor. Experimental results verify that the proposed control approach is very good for complex and non-linear systems. ; Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK)


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    DSP-based sliding mode speed control of induction motor using neuro-genetic structure



    Erscheinungsdatum :

    2009-01-01


    Anmerkungen:

    5540



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




    Induction motor field orientation using sliding mode control

    Melkebeek, J. A. | British Library Conference Proceedings | 1994


    Fractional Order Sliding Mode Speed Control of Feedback Linearized Induction Motor

    Fetene, Yeshiwas / Shibeshi, Dereje | Online Contents | 2020


    Research on Speed Identification of Induction Motor Based on Sliding Mode Observer

    Xu, Qiwei / Zhao, Meng / Luo, Xiaoxiao et al. | Springer Verlag | 2017


    Hybrid Neural Sliding Mode Observer for Speed-Sensor less Control of Induction Motor

    Babaie, Mohammad / Khoshhava, Mojtaba Ayaz / Abarzadeh, Mostafa et al. | IEEE | 2023