基于模糊自适应PID控制的ATO系统控制算法

为了研究ATO系统控制算法的智能性和高效性,在传统PID算法的基础上,充分考虑到列车系统的非线性和复杂性,结合模糊控制理论能进行实时非线性调节的优点,提出了模糊自适应PID控制算法。并在Matlab/Simulink中建立了ATO系统的仿真模型和算法控制模块。将两种算法分别运用到ATO系统中,对目标速度曲线进行跟踪,从停车精度、追溯性、准时性、节能性、舒适性五个方面对二者的控制性能进行比较分析。仿真结果表明,将模糊自适应PID算法运用到ATO系统中,列车的控制性能能够很好地满足ATO系统的各个性能指标要求。

ATO System Control Algorithm Based on Fuzzy Adaptive PID

In order to research on the intelligence and efficiency of urban rail transit ATO system,by taking the non -linear and complex of train system into consideration on the basis of traditional PID control algorithm,and combined with the advantages of fuzzy control theory that can be adjusted in the real-time non-linear system,the fuzzy adaptive PID control algorithm is proposed,simulation models of ATO system and algorithm control module are established in Simulink.The two algorithms are applied to the ATO system to track the target speed curve,analyze the control performances of the two algorithms from five aspects of precision of parking,traceability,punctuality,energy-saving,degree of comfort.imulation results show that ATO system can perfectly satisfy the five performance requirements under the control of fuzzy adaptive PID algorithm.