Abstract
This paper considers the finite-time tracking control problem for the strict-feedback nonlinear continuous systems involving input saturation and output constraints. A sequence of desired and auxiliary virtual control signals and real control input is designed to derive a representation of the system estimation errors and stabilize the system. The proposed approach is further developed via a finite-time stability theory, barrier Lyapunov function, and neural network approximation scheme to achieve an expected performance of the considered system. According to the proposed scheme, we solve the finite-time tracking control problem of the nonlinear systems with input saturation. Then, a theorem is provided to address that all the signals and system states are bounded, and the system output is driven to track the reference signal in a finite time to a small neighborhood of zero and remains in the predefined compact sets. The effectiveness of the proposed scheme is confirmed via two simulation examples.
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Acknowledgements
This work is partially supported by the National Natural Science Foundation of China (61703051) and the Department of Education of Liaoning Province (LZ2017001).
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Zhao, S., Liang, H., Du, P. et al. Adaptive NN finite-time tracking control of output constrained nonlinear system with input saturation. Nonlinear Dyn 92, 1845–1856 (2018). https://doi.org/10.1007/s11071-018-4167-4
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DOI: https://doi.org/10.1007/s11071-018-4167-4