Robust Model Predictive Control of the Cutterhead System in Tunnel Boring Machines

In this paper, a systematic robust model predictive control structure is designed for the cutterhead system in tunnel boring machines. The main concerns are the robustness of the control system with respect to the external load uncertainty and the handling of the constraints on the driving torques. First, a state-space linear dynamical model of the cutterhead system is developed based on first principles. Then, a robust model predictive control structure is designed to handle the constraints and disturbance under the complex working conditions. Finally, extensive simulations are performed to illustrate the effectiveness of the proposed control system.

[1]  Jin Wang,et al.  Dynamic Modeling and Analysis of Shield TBM Cutterhead Driving System , 2010 .

[2]  S. Joe Qin,et al.  A survey of industrial model predictive control technology , 2003 .

[3]  Antonella Ferrara,et al.  MPC for Robot Manipulators With Integral Sliding Modes Generation , 2017, IEEE/ASME Transactions on Mechatronics.

[4]  Dong Won Lee,et al.  Thermal-Hydraulic Analysis for Conceptual Design of Korean HCCR TBM Set , 2016, IEEE Transactions on Plasma Science.

[5]  Bin Yao,et al.  High-performance adaptive robust control with balanced torque allocation for the over-actuated cutter-head driving system in tunnel boring machine , 2017 .

[6]  Wei Xie,et al.  Robust control of saturating systems with Markovian packet dropouts under distributed MPC. , 2019, ISA transactions.

[7]  Yuanqing Xia,et al.  Disturbance Rejection MPC for Tracking of Wheeled Mobile Robot , 2017, IEEE/ASME Transactions on Mechatronics.

[8]  Jianda Han,et al.  Study on Linear Vibration Model of Shield TBM Cutterhead Driving System , 2014 .

[9]  Gyu-Jin Bae,et al.  Manufacturing of an earth pressure balanced shield TBM cutterhead for a subsea discharge tunnel and its field performance analysis , 2014 .

[10]  Wei Xie,et al.  Robust distributed model predictive control of linear systems with structured time-varying uncertainties , 2017, Int. J. Control.

[11]  Ilya V. Kolmanovsky,et al.  Model Predictive Control for Spacecraft Rendezvous and Docking: Strategies for Handling Constraints and Case Studies , 2015, IEEE Transactions on Control Systems Technology.

[12]  Jamal Rostami,et al.  Modeling of soil movement in the screw conveyor of the earth pressure balance machines (EPBM) using computational fluid dynamics , 2015 .

[13]  Xunyuan Yin,et al.  Distributed moving horizon state estimation of two-time-scale nonlinear systems , 2017, Autom..

[14]  Nan Hou,et al.  Analyses of dynamic characteristics and structure optimization of tunnel boring machine cutter system with multi-joint surface , 2017 .

[15]  Baocang Ding,et al.  Output feedback robust MPC for LPV system with polytopic model parametric uncertainty and bounded disturbance , 2016, Int. J. Control.

[16]  Bo Egardt,et al.  Load Management of Modular Battery Using Model Predictive Control: Thermal and State-of-Charge Balancing , 2017, IEEE Transactions on Control Systems Technology.

[17]  Wei Xie,et al.  Robust MPC for Linear Systems with Structured Time‐Varying Uncertainties and Saturating Actuator , 2017 .

[18]  Maurizio Cirrincione,et al.  Multiple Constrained MPC Design for Automotive Dry Clutch Engagement , 2015, IEEE/ASME Transactions on Mechatronics.

[19]  David Q. Mayne,et al.  Model predictive control: Recent developments and future promise , 2014, Autom..

[20]  Guofang Gong,et al.  The Development of a High-Speed Segment Erecting System for Shield Tunneling Machine , 2013, IEEE/ASME Transactions on Mechatronics.

[21]  Antonella Ferrara,et al.  Asynchronous Networked MPC With ISM for Uncertain Nonlinear Systems , 2017, IEEE Transactions on Automatic Control.