城市轨道列车速度曲线预测函数控制改进算法

为有效解决城市轨道列车速度曲线跟踪控制问题，提出了一种速度曲线预测函数控制改进算法IPFC。所提出的预测函数控制改进算法选用阶跃函数和Morlet小波函数作为基函数，其依据目标速度曲线的变化程度，给出了一种预测函数控制的基函数选择策略，该策略可实现小波与阶跃基函数的切换。除此之外，给出了一种基于系统性能模糊满意度与优化因子的柔化因子非线性自适应在线调整策略，通过调整优化因子能够进一步提升跟踪控制性能。基于大连城市轨道交通12号线中旅顺新港至铁山镇的城市轨道列车速度曲线跟踪控制场景，在硬件在环实验环境下得到的实验结果表明，所提出的IPFC能够显著改善控制系统的控制性能，节能、准时、停车精确、舒适4个性能指标都有明显的改善，特别是准时与精确停车，相比广泛应用于实际的传统改进算法均大幅提升超过了55%。

An improved predictive function control algorithm forvelocity curve of urban rail vehicle

To solve the tracking control problem for velocity curve of urban rail vehicle, an improved predictive function control algorithmIPFC is proposed. Step function and Morlet function are selected as two base functions. According to the change degree of target velocitycurve, a strategy for basis function selection of predictive function control is given, which can switch wavelet and step basis function. Inaddition, an adaptive nonlinear online softening factor adjustment strategy based on the fuzzy satisfaction of system performance andoptimization factor is proposed. This strategy can further improve the tracking control performance by using optimization factor. Takingthe instance of velocity curve tracking control from Lvshun New Port to Tieshan Town pertain of the urban rail transit line No. 12 inDalian as the test object, the hardware-in-the-loop test results show that the proposed IPFC can improve control performance of controlsystem significantly. The quality indexes, such as energy conservation, accurate parking, punctuality and comfort, have obviousimprovement effectiveness, especially for punctual and precise parking. Compared with the traditional improved algorithms widely used inpractice, they are improved to be more than 55% .