Abstract
In this paper, a new adaptive neural dynamic surface control technique with an improved prescribed performance function is proposed for the nonlinear two-inertia system. An improved error transformation function is used to ensure the prescribed output tracking performance, and the neural network (NN) is utilized to estimate the unknown disturbance. The dynamic surface technique simplifies the controller by introducing first-order filters to eliminate “explosion of complexity” inherent in backstepping approach. Simulation results demonstrate the control scheme is effective.
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Acknowledgments
This work is supported by National Nature Science Foundation of China (No.61433003, No.612173150, No.61321002).
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Wang, S., Ren, X. (2016). Adaptive Control with Prescribed Performance for Nonlinear Two-Inertia System. In: Jia, Y., Du, J., Li, H., Zhang, W. (eds) Proceedings of the 2015 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48365-7_45
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DOI: https://doi.org/10.1007/978-3-662-48365-7_45
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