基于多质点模型的动车组精准停车自适应控制

Adaptive control of electric multiple unit for accurate stopping based on multi-mass model

中文关键词  精准停车  多质点模型  动车组  参数自适应控制  输入–输出稳定性

英文关键词  accurate stopping  multi-mass model  electric multiple unit  parameter adaptive control  input-output stability

中文摘要

      精准停车是列车自动驾驶系统的关键技术之一, 有助于提高乘客上下车效率, 降低列车停站晚点风险. 本 文针对动车组精准停车问题, 建立动车组多质点非线性动力学模型, 处理各节车厢因随机且未知的乘车人数分配不 同的制动力. 在此模型的基础上, 利用动车组运行过程中的状态偏差, 设计自适应控制器. 针对模型动态非线性和参 数的未知性, 设计参数的估计律, 对参数值进行实时估计. 根据输入–输出稳定性理论, 通过构建含参数估计误差的 Lyapunov函数, 证明自适应控制算法的渐近稳定性. 仿真结果表明: 基于动车组多质点模型, 参数自适应控制器分配 不同的控制输入给复合控制单元进行协调制动. 该控制方法在实现动车组平稳运行的同时, 使得停车误差在±5 cm 以内.

英文摘要

      As the key technology of the automatic train operation (ATO) system, accurate stopping is helpful for improving the efficiency of boarding or alighting and reducing the risk of train delaying. Aiming at realizing accurate stopping of electric multiple unit (EMU), we established a multi-mass nonlinear dynamics model of EMU to deal with the different braking force due to stochastic and uncertain distribution of passengers along carriages. Further, a parameter adaptive controller was designed by utilizing the state deviation during the EMU operation. The estimation law of parameters was devised to tackle its uncertainty and multi-mass model’s dynamic nonlinearity in real time. According to the input-output stability theory, the asymptotic stability of the control algorithm was proved through constructing the Lyapunov function with respect to the error of parameter estimation. The simulation results show that parameter adaptive controller is able to effectively allocate different inputs to composite control units for coordinated braking based on multi-mass model of EMU. Under the premise of guaranteeing the smooth operation of EMU, the proposed method has controlled the stopping error range within ± 5 cm.