Adaptive neural network control of the Furuta pendulum

Javier Moreno-Valenzuela, Carlos Aguilar-Avelar

    Research output: Chapter in Book/Report/Conference proceedingChapter

    1 Scopus citations

    Abstract

    The purpose of this chapter is to introduce a novel adaptive neural network-based control scheme for the Furuta pendulum. Adaptation laws for the input and output weights are provided. The proposed controller is able to guarantee tracking of a reference signal for the arm while the pendulum remains in the upright position. Using real-time experiments, the new scheme is compared with other control methodologies, therein demonstrating the improved performance of the proposed adaptive algorithm.

    Original languageEnglish
    Title of host publicationIntelligent Systems, Control and Automation
    Subtitle of host publicationScience and Engineering
    PublisherSpringer Netherlands
    Pages93-118
    Number of pages26
    DOIs
    StatePublished - 1 Jan 2018

    Publication series

    NameIntelligent Systems, Control and Automation: Science and Engineering
    Volume88
    ISSN (Print)2213-8986
    ISSN (Electronic)2213-8994

      Fingerprint

    Cite this

    Moreno-Valenzuela, J., & Aguilar-Avelar, C. (2018). Adaptive neural network control of the Furuta pendulum. In Intelligent Systems, Control and Automation: Science and Engineering (pp. 93-118). (Intelligent Systems, Control and Automation: Science and Engineering; Vol. 88). Springer Netherlands. https://doi.org/10.1007/978-3-319-58319-8_6