为解决控制盾构导向偏差时既要保证盾构推进速度稳定又要控制导向偏差的问题，研发一种基于粒子群算法的模糊掘进纠偏控制算法，实现盾构设备自动掘进纠偏。首先，基于掘进数据和经验建立纠偏模糊控制规则，实现盾构导向纠偏控制合力和总推进力增量的输出；然后，以纠偏合力和总推进力为求解目标，采用粒子群算法对分区油缸目标控制压力进行求解；最后，采用PID控制器，实现油缸压力的闭环控制，保证盾构掘进纠偏稳定运行。通过在南昌地铁中铁1182号土压平衡盾构测试应用，单环纠偏目标和目标推进速度在每环开始前进行设定，研发的盾构掘进纠偏控制系统实现了连续环自动掘进纠偏控制，其中单环纠偏误差控制在±2 mm，连续环平均误差控制在±1 mm，推进速度平均波动在±5 mm/min。

Controlling guide deviation in shield tunneling necessitates maintaining a stable shield propulsion speed and precise deviation control. To address this, a fuzzy tunneling deviation control algorithm utilizing particle swarm optimization(PSO) has been developed. Initially, fuzzy deviation control rules are formulated based on tunneling data and experience, which facilitate the output of both the correction force and the total propulsion force increment necessary for deviation control. Subsequently, the PSO algorithm calculates the target control pressure of the sectional cylinders, using the correction force and total propulsion force as optimization objectives. A proportionalintegralderivative controller then performs closedloop control of the cylinder pressure, ensuring stable operation of the shield tunneling deviation correction system. This system was applied and evaluated during the earth pressure balance shield tunneling on Nanchang metro line CREC 1182. Prior to ring propulsion, the deviation target for each ring and the target propulsion speed are preset. The system enables continuous automatic tunneling deviation control for each ring, maintaining a deviation error within ±2 mm for individual rings and an average error below ±1 mm across successive rings. The average fluctuation of the propulsion speed is kept within ±5 mm/min.