Abstract
In this paper, the problem of fault-tolerant control (FTC) is investigated for a class of nonlinear single input and single output (SISO) systems in the non-strict feedback form. The considered system possess unknown nonlinear functions, unmeasured states, unknown time-varying delays, unknown control direction and actuator faults (bias and gain faults). Neural networks (NNs) are adopted to approximate the unknown nonlinear functions. Then, a state observer is constructed to solve the problem of unmeasured states. In the frame of adaptive backstepping design technique, by combining with Nussbaum gain function and Lyapunov-Krasobskii functional theory, an adaptive NNs output feedback FTC method is developed. It is shown that all signals in the closed-loop system are proved to be bounded, and the system output can follow the given reference signal well.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (Nos. 61573175, 61572244) and Liaoning BaiQianWan Talents Program.
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Dong, G., Li, Y., Meng, D., Sun, F., Bai, R. (2017). Adaptive NNs Fault-Tolerant Control for Nonstrict-Feedback Nonlinear Systems. In: Cong, F., Leung, A., Wei, Q. (eds) Advances in Neural Networks - ISNN 2017. ISNN 2017. Lecture Notes in Computer Science(), vol 10262. Springer, Cham. https://doi.org/10.1007/978-3-319-59081-3_2
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DOI: https://doi.org/10.1007/978-3-319-59081-3_2
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