An autonomous attitude control system, utilizing a
combination of artificial intelligence and traditional control theory, is
proposed to enhance the quality of tunnels formed and minimize environmental
disruption during the excavation process. To achieve this, the control system
is divided into two layers: planning and execution. The planning layer employs
a collection experience modal decomposition method to process the highfrequency
signal in the original data in a stable manner. After training the historical
and realtime data, a shield motion model is
established to plan the control trajectory based on the design axis. In the
execution layer, a position controller model is built using a neural network,
and the advancing parameters are adjusted according to realtime feedback, allowing for the prediction and autonomous control of
the shield attitude. The system was implemented in the ZhiYu shield excavation
control system, utilized in the leftline of the KeqiaoDiyang section of the HangzhouShaoxing
metro tunnel project. The results demonstrate that the proposed control system
outperforms the manual control method in terms of stability and prediction
accuracy. The autonomous attitude control system presents a promising solution
to enhance tunnel excavation processes and reduce environmental disturbance.
WU Bingjian
,
WU Huiming
,
HU Min
,
SUN Junchao
. Design and Application of a Data Driven
Shield Autonomous Attitude Control System[J]. Tunnel Construction, 2023
, 43(3)
: 478
-485
.
DOI: 10.3973/j.issn.2096-4498.2023.03.012
