Abstract
In this paper, an observer-based adaptive control scheme for a class of nonlinear systems with parametric uncertainties is proposed. The adaptive observers using parameter estimates ensure the identification errors of system states are convergent to zero, and force the parameter estimates approach to the true values especially if the observer gains are selected large enough. By combining the Lyapunov synthesis with backstepping framework, the global asymptotical stability and bounded signals of the resulting closed-loop system can be ensured. A numerical example is employed to demonstrate the effectiveness of the proposed adaptive control scheme.
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© 2015 Springer International Publishing Switzerland
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Sun, JC., Wang, N., Liu, YC. (2015). Adaptive Control of a Class of Nonlinear Systems with Parameterized Unknown Dynamics. In: Hu, X., Xia, Y., Zhang, Y., Zhao, D. (eds) Advances in Neural Networks – ISNN 2015. ISNN 2015. Lecture Notes in Computer Science(), vol 9377. Springer, Cham. https://doi.org/10.1007/978-3-319-25393-0_9
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DOI: https://doi.org/10.1007/978-3-319-25393-0_9
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