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.
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Moreno-Valenzuela, J., Aguilar-Avelar, C. (2018). Adaptive Neural Network Control of the Furuta Pendulum. In: Motion Control of Underactuated Mechanical Systems. Intelligent Systems, Control and Automation: Science and Engineering, vol 88. Springer, Cham. https://doi.org/10.1007/978-3-319-58319-8_6
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DOI: https://doi.org/10.1007/978-3-319-58319-8_6
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-58318-1
Online ISBN: 978-3-319-58319-8
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