Abstract
In this paper, the adaptive control problem with input saturation is investigated for double inverted pendulums. Based on Lyapunov stability theory and backstepping technique, incorporating dynamic surface control (DSC) technique into neural network based adaptive control, an adaptive neural controller is developed by explicitly considering uncertainties, unknown disturbances and input saturation. An auxiliary system is presented to tackle input saturation, and the states of auxiliary design system are utilized to develop the tracking control. It is proved that all the signals in the closed-loop system are uniformly ultimately bounded (UUB) via Lyapunov analysis. Finally, simulation studies are given to demonstrate the effectiveness of the proposed method.
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Yang, W., Wu, J., Yang, S., Tao, Y. (2013). Adaptive NN Tracking Control of Double Inverted Pendulums with Input Saturation. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39068-5_18
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DOI: https://doi.org/10.1007/978-3-642-39068-5_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39067-8
Online ISBN: 978-3-642-39068-5
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