To optimize attitude trajectory correction during
shield excavation, a composite control method based on selfdisturbance
rejection control and Qlearning optimization is
proposed. This is because the shieldtunneling posture
considerably affects tunnel formation and excavation efficiency,strong coupling
and nonlinearity that affect the excavation posture in practice are complex and
difficult to distinguish, and steadystate effect of
conventional parameter adjustment methods is insufficient. The proposed control
method involves the mathematical modeling of the pressure regulation zones of
the shield oil cylinder and designing of a linear selfdisturbance
rejection controller. Based on the selfdisturbance
rejection control framework, the Qlearning algorithm
is used to achieve adaptive tuning of controller parameters. The effectiveness
of the proposed method is validated through model simulations, providing
technical insights for developing device control programs. Compared with the
traditional proportionalintegralderivative and selfdisturbance rejection
controls, the proposed method achieves adaptive parameter debugging and
improves the control performance of the deviation correction attitude of
shield.
ZHAO Wenjia
,
SHI Xiaowei
,
ZHAO Qian
,
YANG Lu
,
ZHANG Yanli
,
ZHANG Yimin
. Shield Deviation Correction Control Based on Active
Disturbance Rejection Control and QLearning[J]. Tunnel Construction, 2024
, 44(2)
: 282
-287
.
DOI: 10.3973/j.issn.2096-4498.2024.02.007
