High-speed train cooperative control based on fractional-order sliding mode adaptive algorithm

Junting Lin, Mingjun Ni, Huadian Liang
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引用次数: 1

Abstract

PurposeThis study aims to propose an adaptive fractional-order sliding mode controller to solve the problem of train speed tracking control and position interval control under disturbance environment in moving block system, so as to improve the tracking efficiency and collision avoidance performance.Design/methodology/approachThe mathematical model of information interaction between trains is established based on algebraic graph theory, so that the train can obtain the state information of adjacent trains, and then realize the distributed cooperative control of each train. In the controller design, the sliding mode control and fractional calculus are combined to avoid the discontinuous switching phenomenon, so as to suppress the chattering of sliding mode control, and a parameter adaptive law is constructed to approximate the time-varying operating resistance coefficient.FindingsThe simulation results show that compared with proportional integral derivative (PID) control and ordinary sliding mode control, the control accuracy of the proposed algorithm in terms of speed is, respectively, improved by 25% and 75%. The error frequency and fluctuation range of the proposed algorithm are reduced in the position error control, the error value tends to 0, and the operation trend tends to be consistent. Therefore, the control method can improve the control accuracy of the system and prove that it has strong immunity.Originality/valueThe algorithm can reduce the influence of external interference in the actual operating environment, realize efficient and stable tracking of trains, and ensure the safety of train control.
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基于分数阶滑模自适应算法的高速列车协同控制
本研究旨在提出一种自适应分数阶滑模控制器,解决运动块系统在扰动环境下的列车速度跟踪控制和位置区间控制问题,以提高跟踪效率和避碰性能。基于代数图论,建立了列车间信息交互的数学模型,使列车能够获取相邻列车的状态信息,从而实现对各列车的分布式协同控制。在控制器设计中,将滑模控制与分数阶演算相结合,避免了不连续切换现象,从而抑制了滑模控制的抖振,并构造了参数自适应律来近似时变工作阻力系数。仿真结果表明,与比例积分导数(PID)控制和普通滑模控制相比,该算法在速度方面的控制精度分别提高了25%和75%。在位置误差控制中减小了算法的误差频率和波动范围,误差值趋于0,运行趋势趋于一致。因此,该控制方法可以提高系统的控制精度,并证明其具有较强的抗扰性。该算法可以减少实际运行环境中外界干扰的影响,实现列车的高效稳定跟踪,保证列车控制的安全性。
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