| Modeling, Simulation, Analysis, and Decision |
|
|
|
|
| Controller design for the hybrid cutterhead driving system of TBMunder limited rotational speed condition |
| WANG Fei, GONG Guo-fang, QIN Yong-feng |
| State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, China |
|
|
|
Abstract The conventional cutterhead rotational speed control strategy of TBM (tunnel boring machine) designed for the single driving source of variable frequency motor causes serious bias load in the hybrid cutterhead mechanical transmission system, which decreases the component’s lifespan and TBM availability. Considering the constraints in the rotational speed and the parameter drift in the excavation process, an adaptive control strategy was used to design a rotational speed control system based on driving source torque control for the the electro-hydraulic hybrid cutterhead driving system (EHDS). The model of the gear-ring transmission system was established. The parametric uncertainty in the system was considered. The MATLAB/AMESim co-simulations results showed that the proposed adaptive control system could compensate the parameter drift, realized the load torque distribution between different types of driving sources while realizing the precise control of the cutterhead rotational speed. The bias load phenomena had been eliminated by the proposed adaptive control system. EHDS can effectively improve its geological adaptability and play an important role in improving the driving speed by complementing the driving characteristics of hydraulic motor and variable frequency motor.
|
|
Received: 27 March 2019
Published: 28 December 2019
|
|
|
转速受限条件下TBM刀盘混合驱动系统控制器设计
传统全断面硬岩隧道掘进机（tunnel boring machine, TBM）刀盘转速同步控制方法是针对变频电机单一驱动源进行设计的，直接应用于混合驱动型TBM刀盘驱动系统易导致齿轮齿圈发生严重的偏载，显著降低TBM刀盘传动系统的使用寿命和TBM设备完好率。考虑到实际掘进过程中对刀盘转速的限制和系统参数漂移，采用自适应控制策略，针对电液混合驱动型TBM刀盘驱动系统设计基于驱动源力矩控制的转速控制方法。建立了齿轮齿圈传动系统模型，系统的参数不确定性得到充分考虑。通过MATLAB/AMESim联合仿真表明，该自适应控制系统对参数漂移具有补偿作用，在精确控制刀盘转速的同时，实现了不同类型驱动源间的负载力矩分配，原系统中的偏载问题得到了解决。电液混合驱动型TBM刀盘驱动系统通过液压马达和变频电机两种驱动源驱动特性的互补，有效提高了其地质适应性，并对提高掘进速度有着重要的作用。
关键词：
刀盘驱动,
TBM,
自适应控制,
负载力矩分配
|
|
[1] 周赛群.全断面硬岩掘进机（TBM）驱动系统研究[D]. 杭州:浙江大学机械工程学院, 2008：10-17. ZHOU Sai-qun. Sudy on drive system of tunnel boring machine[D]. Hangzhou：Zhejiang University, School of Mechanical Engineering， 2008： 10-17.
[2] MAIDL Bernhard, SCHMID Leonhard, RITZ Willy, et al. Hardrock tunnel boring machines[M]. Hamburg： John Wiley & Sons, 2008：17-29.
[3] LIAO Jian-feng, CHEN Zheng, YAO Bin. High-performance adaptive robust control with balanced torque allocation for the over-actuated cutter-head driving system in tunnel boring machine[J]. Mechatronics, 2017, 46: 168-176. doi:10.1016/j.mechatronics.2017.08.007
[4] JAMSHIDI A. Prediction of TBM penetration rate from brittleness indexes using multiple regression analysis[J]. Modeling Earth Systems and Environment, 2018, 4 (1): 383-394. doi:10.1007/s40808-018-0432-2
[5] XIE Hai-bo, GONG Hua-sheng, HU Liang, et al. Improving the extricating performance of TBM cutter-head driving system with hydro-viscous clutch[C]// 2016 12th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), Auckland，Aug. 29-31， 2016. doi:10.1109/MESA.2016.7587188
[6] WU Han-yang, HUO Jun-zhou, ZHANG Wei, et al. An electromechanical coupling model of TBM's main driving system[C]// 2016 12th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), Auckland，Aug. 29-31， 2016. doi:10.1109/MESA.2016.7587111
[7] GONG Qiu-ming, YIN Li-jun, MA Hong-su, et al. TBM tunnelling under adverse geological conditions: an overview[J]. Tunnelling and Underground Space Technology, 2016, 57：4-17. doi:10.1016/j.tust.2016.04.002
[8] LIU Tong,GONG Guo-fang,PENG Zuo, et al. Modeling and intelligent synchronous control for parallel-connected motor-gear driving system of TBM cutterhead[C]//Mechanics and Mechanical Engineering: Proceedings of the 2015 International Conference (MME2015)， Chengdu， Dec. 25-27， 2015. doi:10.1142/9789813145603_0111
[9] SHAO Cheng-jun, LIAO Jian-feng, LI Xiu-liang, et al. An adaptive robust control for hard rock tunnel boring machine cutterhead driving system[C]// ASME 2015 Dynamic Systems and Control Conference, Columbus， Oct. 28-30， 2015. doi:10.1115/DSCC2015-9697
[10] SUN Dong, SHAO Xiao-yin, FENG Gang. A model-free cross-coupled control for position synchronization of multi-axis motions: theory and experiments[J]. IEEE Transactions on Control Systems Technology, 2007, 15 (2): 306-314. doi:10.3182/20050703-6-cz-1902.00400
[11] ZHANG Cheng-hui, SHI Qing-sheng, CHENG Jin. Synchronization control strategy in multi-motor systems based on the adjacent coupling error[J]. Proceedings of the Chinese Society of Electrical Engineering, 2007（15）: 59-63. doi:10.1360/aas-007-0331
[12] ZHANG Kai-zhi, YU Hai-dong, LIU Zhong-po, et al. Dynamic characteristic analysis of TBM tunnelling in mixed-face conditions[J]. Simulation Modelling Practice and Theory, 2010, 18 (7): 1019-1031. doi:10.1016/j.simpat.2010.03.005
[13] KAWAMURA Atsuo, ITOH Hiroshi, SAKAMOTO Kiyoshi. Chattering reduction of disturbance observer based sliding mode control[J]. IEEE Transactions on Industry Applications, 1994, 30 (2): 456-461. doi:10.1109/28.287509
[14] LI Hong-yi, SHI Peng,YAO De-yin, et al. Observer-based adaptive sliding mode control for nonlinear Markovian jump systems[J]. Automatica, 2016, 64： 133-142. doi:10.1016/j.automatica.2015.11.007
[15] LIAO Jian-feng, YAO Bin, ZHU Xiao-cong. Adaptive robust coordinated control for over-actuated cutter-head driving systems of hard rock tunnel boring machines[J]. IFAC-PapersOnLine, 2016, 49 (21): 611-616. doi:10.1016/j.ifacol.2016.10.668
[16] YAO Bin, TOMIZUKA Masayoshi. Adaptive robust control of SISO nonlinear systems in a semi-strict feedback form[J]. Automatica, 1997, 33 (5): 893-900. doi:10.1016/s0005-1098(96)00222-1
[17] CHEN Shan, CHEN Zheng, YAO Bin, et al. Adaptive robust cascade force control of 1-DOF hydraulic exoskeleton for human performance augmentation[J]. IEEE/ASME Transactions on Mechatronics, 2017, 22 (2): 589-600. doi:10.1109/TMECH.2016.2614987
[18] LYNN Alfred, SMID Edzko, ESHRAGHI Moji, et al. Modeling hydraulic regenerative hybrid vehicles using AMESim and Matlab/Simulink[C]// Enabling Technologies for Simulation Science IX, 2005: 24-41. doi:10.1117/12.603712 |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
