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Diagnostic model of electric multiple units brake control system based on particle swarm optimization

机译:基于粒子群优化的电多单位制动控制系统诊断模型

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摘要

In order to explore the application of particle swarm optimization (PSO) in the control of electric multiple unit (EMU) brake control system, the principle of EMU braking system, block partition and Quantum swarm optimization (QSO) is understood. PSO is applied to the diagnosis model of EMU braking process, and then the data are analyzed through computer simulation experiments. The results show that PSO algorithm has obvious effect on the diagnosis model of EMU braking process under railway block partition. When using PSO, the number of iterations of EMU braking system model to achieve convergence equilibrium is much less than that of ordinary model, which has obvious rapidity and ease of implementation and has great significance especially in safety. In summary, PSO is very suitable for being applied the diagnosis model of EMU brake control system.
机译:为了探讨粒子群优化(PSO)在电动多单元(EMU)制动控制系统中的应用中,理解EMU制动系统,块分区和量子群优化(QSO)的原理。 PSO适用于EMU制动过程的诊断模型,然后通过计算机仿真实验分析数据。结果表明,PSO算法对铁路块分区诊断模型对EMU制动过程的诊断模型有明显影响。使用PSO时,EMU制动系统模型的迭代次数以实现收敛均衡远低于普通模型的次数,这具有明显的速度和易于实现,特别是在安全方面具有重要意义。总之,PSO非常适合应用EMU制动控制系统的诊断模型。

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