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All Journal Journal of Fuzzy Systems and Control (JFSC)
Van Khuong, Huynh
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Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Nonlinear Control Law Design for Inverted Pendulum Systems via RBF Neural Networks Van Khuong, Huynh; Chiem, Nguyen Xuan; Obukhov, Alexander
Journal of Fuzzy Systems and Control Vol. 3 No. 2 (2025): Vol. 3, No. 2, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i2.314

Abstract

This paper presents the design of a nonlinear control law based on the Backstepping method combined with Radial Basis Function (RBF) neural networks to ensure the stability of an inverted pendulum system with unknown model parameters. The control design is developed using a general form of the system’s mathematical model, in which the unknown nonlinear functions are approximated by RBF neural networks. Experimental results conducted on the STM32F4 embedded platform demonstrate that the proposed approach not only guarantees system stability but also verifies the effectiveness and practical applicability of the control law.
Co-Authors Chiem, Nguyen Xuan Obukhov, Alexander