基于特征模型的高速列车自适应误差补偿控制
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1.华东交通大学电气与自动化工程学院;2.华东交通大学

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国家自然科学基金资助项目(62003138,U2034211);江西省自然科学(20202BAB202005);江西省研究生创新专项资金项目(YC2021-S447)


Characteristic Model Based Adaptive Error Compensation Control for High-speed Train
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    摘要:

    针对高速列车运行过程中因不确定运行阻力和模型误差等因素产生的系统误差,提出了新的基于特征模型的高速列车自适应误差补偿控制策略,实现了其对给定目标速度曲线的渐近跟踪。首先通过动力学分析,基于特征建模方法和参数辨识,建立了存在系统误差的高速列车特征模型;其次,利用扩张状态观测器对系统误差的估计能力,设计了基于特征模型的高速列车自适应误差补偿控制器,并结合广义最小方差方法对控制器参数进行了优化,使其在存在系统误差时仍能实现对给定速度曲线的渐近跟踪。该控制策略能够有效处理系统误差带来的不确定性,提高控制精度,从而保障高速列车的安全可靠运行。为了验证本文所提方法的有效性,以CRH380A型高速列车为被控对象进行仿真实验。仿真结果表明本文设计的补偿控制方法在列车存在未知系统误差的情况下仍能保证理想的控制性能。

    Abstract:

    Aiming at the system errors caused by uncertain running resistances, model errors and other factors during the high-speed train operation, a new adaptive error compensation control scheme based on characteristic model is proposed to realize the asymptotic tracking of a given target speed curve. Firstly, the characteristic model of high-speed train with system errors is derived based on the characteristic modeling method and the parameter identification by the dynamic analysis of high-speed train. Secondly, an adaptive error compensation controller for high-speed train based on the characteristic model is designed by employing the ability of the extended state observer for the system error estimations, and the controller parameters are optimized based on the generalized minimum variance method, to achieve asymptotic tracking of a given speed profile even in the presence of the system errors. Such a control strategy can effectively deal with the uncertainties caused by system errors, improve the control accuracy, and guarantee the safe and reliable operation of high-speed train. To verify the effectiveness of the method proposed in this paper, simulation experiments are conducted by using the CRH380A type high-speed train as the controlled object. Simulation results show that the compensation control method designed in this paper has desired control performance despite the existence of unknown system errors.

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  • 收稿日期:2022-10-21
  • 最后修改日期:2022-11-29
  • 录用日期:2022-12-06
  • 在线发布日期: 2023-06-21
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