Data-Based Dynamic Decoupling Control for MIMO Precision Motion Stages With Position-Dependent Disturbances

Decoupling control is a widely employed technique used to mitigate coupling effects and bridge the gap between multiple-input multiple-output (MIMO) and single-input single-output (SISO) control. In the field of precision motion control, the cross-talk resulting from coarse decoupling poses a significant challenge to achieving high performance. Static decoupling control fails to completely decouple the MIMO system due to dynamic disparities between drives, actuators, and the flexible modes of the plant. Consequently, dynamic decoupling control methods have gained attention for their potential to enhance performance. However, existing dynamic decoupling control methods suffer from limitations such as reliance on system models, and susceptibility to disturbances and noise. In this paper, these deficiencies are addressed by 1) a data-based optimization with no involvement of model knowledge, and 2) using the augmented vector and instrumental variable to eliminate the estimation bias caused by position-dependent disturbances and measurement noise. The effectiveness and superiority of the proposed method are substantiated through numerical simulations and experiments conducted on an ultra-precision wafer stage.