Data-Based Iterative Tuning of Feedforward Control With Disturbance Compensation for Dual-Drive Gantry Stages in Wafer Inspection

The increasingly high requirements for control performance and inevitable external disturbances, specifically cable force and force ripple, pose challenges to the motion control of dual-drive gantry stages. Preexisting control methods either fail to adapt to varying tasks or suffer from performance limitations due to the lack of disturbance consideration. To address these issues, this article proposes a novel data-based iterative feedforward tuning approach that incorporates disturbance compensation for both cable force and force ripple. First, the feedforward controller and disturbance compensator are parameterized following a thorough dynamic analysis of the gantry stage. A new parameter tuning method is then developed, iteratively updating all parameters of both the feedforward controller and disturbance compensator using the measured feedback control signal from previous tasks. The proposed approach is implemented in the Matlab/Simulink environment and deployed on the dSPACE MicroLabBox (DS1202) real-time hardware system. Experimental validation on an industrial dual-drive gantry stage for wafer defect inspection demonstrates the superior performance of the proposed method, achieving higher tracking accuracy compared to preexisting data-based iterative feedforward tuning and greater robustness against varying tasks compared to iterative learning control.