Abstract
Based on the backstepping method and the neural networks (NNs) technique, a direct adaptive controller is proposed for a class of nonlinear fin stabilizer system in this paper. This approach overcomes the uncertainty in the nonlinear fin stabilizer system and solves the problems of mismatch and controller singularity. The stability analysis shows that all the signals of the closed-loop system are uniformly ultimate boundedness (UUB). A simulation example is given to illustrate the effectiveness of the proposed method.
This work was supported in part by the National Natural Science Foundation of China (Nos.51179019, 60874056), the Natural Science Foundation of Liaoning Province (No. 20102012) and the Program for Liaoning Excellent Talents in University (LNET) (Grant No.LR2012016), the Fundamental Research Funds for the Central Universities (No. 3132013005), and the Applied Basic Research Program of Ministry of Transport of China.
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Bai, W., Li, T., Gao, X., Myint, K.T. (2013). Neural Network Based Direct Adaptive Backstepping Method for Fin Stabilizer System. 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_26
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DOI: https://doi.org/10.1007/978-3-642-39068-5_26
Publisher Name: Springer, Berlin, Heidelberg
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