Abstract
The running process of high-speed train is a complex, multivariable, and nonlinear dynamic system with many uncertain factors. Nonlinear, time-varying and other factors make it difficult to achieve the desired performance with the linear time-invariant feedback controller. A class of adaptive learning control method is proposed to solve the problem of unknown time varying in high-speed train operation. The parametric system is used to describe the high-speed train dynamics model, and the nonlinear characteristics of the system are studied. A parameter-adaptive learning control method is given. Based on the Lyapunov functional analysis method, it is proved that the adaptive learning control method and its improved form can guarantee the train to converge to the desired speed trajectory every point. Finally, numerical simulations are conducted to verify the effectiveness of the proposed method.
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Acknowledgements
The project was supported by the National Natural Science Foundation of China (Grant No. 61463013).
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Yang, D., Niu, L. (2018). Adaptive Control with Asymptotic Stability Guarantees for High-Speed Train Systems with Uncertain Input Nonlinearities. In: Jia, L., Qin, Y., Suo, J., Feng, J., Diao, L., An, M. (eds) Proceedings of the 3rd International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2017. EITRT 2017. Lecture Notes in Electrical Engineering, vol 483. Springer, Singapore. https://doi.org/10.1007/978-981-10-7989-4_99
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DOI: https://doi.org/10.1007/978-981-10-7989-4_99
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