WOS: 000398510500001 ; In this article, a novel real-time artificial neural network-based adaptable switching dynamic controller is developed and practically implemented. It will be used for real-time control of two-wheeled balance robot which can balance itself upright position on different surfaces. In order to examine the efficiency of the proposed controller, a two-wheeled mobile balance robot is designed and a test platformfor experimental setup ismade for balance problemon different surfaces. In a developed adaptive controller algorithm which is capable to adapt different surfaces, mean absolute target angle deviation error, mean absolute target displacement deviation error andmean absolute controller output data areemployed for surface estimation by using artificial neural network. In a designed two-wheeledmobile balance robot system, robot tilt angle is estimated viaKalman filter from accelerometer and gyroscope sensor signals. Furthermore, a visual robot control interface is developed in C++ software development environment so that robot controller parameters can be changed as desired. In addition, robot balance angle, linear displacement and controller output can be observed online on personal computer. According to the real-time experimental results, the proposed novel type controller gives more effective results than the classic ones.


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    Titel :

    Adaptive control of two-wheeled mobile balance robot capable to adapt different surfaces using a novel artificial neural network-based real-time switching dynamic controller


    Beteiligte:

    Erscheinungsdatum :

    2017-01-01


    Anmerkungen:

    2



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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