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首页> 外文会议>Chinese Automation Congress >Adaptive Tracking Control with Input Saturation and Asymmetrically Time-varying Full-State Constraints for Automatic Train Operation
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Adaptive Tracking Control with Input Saturation and Asymmetrically Time-varying Full-State Constraints for Automatic Train Operation

机译：输入饱和和非对称时变全状态约束的自适应跟踪控制，可实现自动列车运行

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摘要

The state feedback tracking control problem is investigated for the train with traction and braking saturation under asymmetrically time-varying full-state constraints. To reduce the influence of input constraint, the saturation function is approximated as the sum of a smooth function and a error term. Moreover, an asymmetrically time-varying Barrier Lyapunov function is adopted to deal with the state constraints. Meanwhile, RBF and adaptive control method have been used to approximate the unknown function and estimate the unknown parameters. Hence, the proposed control method can ensure that all the signals in the close-loop system are bounded and the asymmetrically time-varying state constraints have not been violated. At last, the simulation exmaple of the train operating in fast strategy and running in the wind zone demonstrates the effectiveness of the control method.
机译：研究了在非对称时变全状态约束下具有牵引力和制动饱和度的列车的状态反馈跟踪控制问题。为了减少输入约束的影响，将饱和度函数近似为平滑函数和误差项的总和。此外，采用非对称时变屏障李雅普诺夫函数来处理状态约束。同时，RBF和自适应控制方法已被用于近似未知函数并估计未知参数。因此，所提出的控制方法可以确保闭环系统中的所有信号都受到限制，并且不违反非对称时变状态约束。最后，以快速策略运行并在风区中运行的列车的仿真实例证明了该控制方法的有效性。

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