介绍了双护盾掘进机推进系统的工作原理,并在AMEsim环境下建立了其液压系统模型,根据实际情况对相关参数进行了优化设计。此外,考虑到系统的时变非线性及复杂工况的影响,采用了基于RBF神经网络的自整定PID控制算法。运用MATLAB软件编写了相应的S函数,通过AMEsim/Sinulink与AMEsim进行了模块化联合仿真分析。结果表明,与常规PID控制相比,该控制器易于实现PID参数的自整定,能明显改善系统的鲁棒性和适应能力。 The working principle of double shield TBM propulsion system was introduced. The hydraulic system model was established under AMEsim environment. The relevant parameters were optimized according to the actual situation. In addition, taking into account the system time-varying nonlinear and complex conditions, the use of self-tuning PID control algorithm based on RBF neural network. The corresponding S functions were programmed by using MATLAB software and the modular co-simulation analysis was carried out by AMEsim / Sinulink and AMEsim. The results show that compared with the conventional PID control, the controller is easy to self-tuning PID parameters, which can obviously improve the robustness and adaptability of the system.