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| Adaptive PID control for thrust speed of the shield based on BP neural networks |
| LIU Guo-Bin, GONG Guo-Fang, ZHU Bei-Dou, SHI Hu |
| Department of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China |
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Abstract As the geology is variable in shield tunneling process, the control of thrust speed must be nonlinear, which puts forward higher requirement for control algorithm. The model for thrust speed of the thrust hydraulic system in the shield was established, lying on the analysis of the theory of the thrust hydraulic system of the shield. An adaptive PID controller for thrust speed of the thrust hydraulic system in the shield based on BP neural networks was designed and the step response simulation was carried out by use of MATLAB software under two different methods of controlling for thrust speed of the shield which were traditional PID control and adaptive PID control based on BP neural networks, the sinusoidal tracking simulation was also performed. The simulated results show that PID controller tuned by BP neural networks has good tracking abilities, strong robustness and higher stable precision, better ability for setting than traditional PID control. Therefore, adaptive PID control based on BP neural networks applies to such nonlinear application case as the control of thrust speed of the shield．
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Published: 28 December 2010
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基于BP神经网络的盾构推进速度自适应PID控制
盾构掘进过程中地质多变,推进速度要求实现非线性控制,因此对控制方法提出较高的要求.在分析了盾构推进液压系统原理的基础上,建立了盾构推进速度仿真模型,设计了基于BP神经网络的盾构推进速度自适应PID控制器,运用MATLAB软件对常规PID推进速度控制和基于BP神经网络的自适应PID推进速度控制进行了阶跃响应仿真对比,并对基于BP神经网络的自适应PID推进速度控制的正弦跟踪特性进行了仿真.仿真结果表明基于BP神经网络整定的PID控制具有良好的跟踪能力和鲁棒性,相比于传统PID控制系统响应迅速,超调量小,具有很高的响应精度和良好的在线整定能力,对于盾构推进速度这种非线性过程,控制效果比较理想.
关键词：
盾构,
推进液压系统,
推进速度,
BP神经网络,
PID
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