Abstract
A disturbance-observer-based adaptive neural network (ANN) control scheme is discussed for the discrete-time nonlinear system with strict-feedback form in this paper. To monitor the external disturbance, a disturbance observer (DO) is proposed. Then, an ANN controller is developed with the outputs of the DO and the radial basis function neural network (RBFNN). The bounded stability of the whole closed-loop system is guaranteed by choosing the appropriate parameters. At last, the validity of the proposed control scheme is verified by a numerical simulation.
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Acknowledgments
This research is supported by Jiangsu Natural Science Foundation of China (No. BK20171417).
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Wu, B., Chen, M., Zhu, R. (2020). Adaptive NN Control of Discrete-Time Nonlinear Strict-Feedback System Using Disturbance Observer. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2019 Chinese Intelligent Systems Conference. CISC 2019. Lecture Notes in Electrical Engineering, vol 592. Springer, Singapore. https://doi.org/10.1007/978-981-32-9682-4_8
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DOI: https://doi.org/10.1007/978-981-32-9682-4_8
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