U ovome redu predstavljen je neuro-adaptivni regulator za žično pogonjene paralelne robote. Robusni neuro-adaptivni regulator sastoji se od računalnog regulatora i robusnog regulatora. Računalni regulator koji sadrži estimator s neuronskom mrežom s radijalnom aktivacijskom funkcijom je glavni regulator u "on-line" metoda podešavanja parametara neuronske mreže za estimaciju dinamike sustava upravljanja. Efikasnost sustava adaptivnog, robusnog regulatora testirana je na na žično pogonjenom paralelnom robotu. Simulacijski rezultati pokazuju da se predloženim robusnim i adaptivnim regulatorom mogu dobiti zadovoljavajuće performance prilikom slijeđenja. ; In this study, a robust neuro-adaptive controller for cable-driven parallel robots is proposed. The robust neuro-adaptive control system is comprised of a computation controller and a robust controller. The computation controller containing a neural-network-estimator with radial basis function activator is the principal controller and the robust controller is designed to achieve tracking performance. An on-line tuning method is derived to tune the parameters of the neural network for estimating the controlled system dynamic function. To investigate the effectiveness of the robust adaptive control, the design methodology is applied to control a cable-driven parallel robot. Simulation results demonstrate that the proposed robust adaptive control system can achieve favorable tracking performances for the robot.


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    Titel :

    Dizajn robusnog neuro-adaptivnog regulatora za žično pogonjene paralelne robote ; On The Design of The Robust Neuro-Adaptive Controller for Cable-driven Parallel Robots


    Beteiligte:
    Barhaghtalab, Mojtaba Hadi (Autor:in) / Bayani, Hassan (Autor:in) / Nabaei, Armin (Autor:in) / Zarrabi, Houman (Autor:in) / Amiri, Ali (Autor:in)

    Erscheinungsdatum :

    23.03.2017


    Anmerkungen:

    Automatika : časopis za automatiku, mjerenje, elektroniku, računarstvo i komunikacije ; ISSN 0005-1144 (Print) ; ISSN 1848-3380 (Online) ; Volume 57 ; Issue 3


    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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