Data-Driven Motion Control For Ultra-Precision Motion Stages Of Lithographic Scanners

The ultra-precision motion stage is an important mechatronic unit of industrial lithographic scanners for manufacturing integrated circuits,and its excellent tracking performance is the key to ensure the throughput and resolution.Consequently,the motion control study for the ultra-precision motion stage possesses important theoretical significance and engineering application value.However,the motion control of the ultra-precision motion stage is confronted with the following three technical challenges: it is hard to take into account both small settling time and insensitivity to reference variations;moving average(MA)and moving standard deviation(MSD)of the tracking error during the exposure phase are contradictory to each other;and it is quite difficult to achieve the performance robustness due to the position-dependent dynamics and disturbances.To solve these problems,this dissertation focuses on the systematic and deep research on the data-driven parameter tuning methods of the feedforward control,variable-gain feedback control,and discrete sliding mode control(DSMC).For the ultra-precision motion stage,the complex and non-minimum phase dynamics lead to the difficulty in simultaneously achieving small settling time and insensitivity to reference variations.To realize small settling time regardless of reference variations,a data-driven zero phase error tracking feedforward control method is synthesized.A new parametric structure containing the model information is first proposed for the feedforward controller.On the basis of instrumental-variable identification method,the correlation between the reference and the tracking error is selected as the optimization criterion,and a data-driven parameter tuning method is developed to achieve the unbiased parameter optimization in noisy environment.Furthermore,the ridge estimate method is employed to guarantee a fast convergent iteration in the case of ill-conditioned Hessian matrix,which results from the non-minimum phase dynamics of the ultra-precision motion stage.To overcome the inherent limitations of linear feedback control and simultaneously improve MA and MSD during the exposure phase,a frequency-dependent variable-gain feedback control method is proposed.The add-on variable-gain elements are designed according to the error frequencies of different reference trajectory phases.For the corresponding nonlinear closed-loop system,the input-state(robust)stability criterion with less conservatism is established via Lyapunov stability theory.Aiming at the parameter optimization problem of the above nonlinear variable-gain feedback controller,a data-driven parameter tuning method with multi-parameter accelerated iterative algorithm is synthesized to achieve the simultaneous optimization of MA and MSD during the exposure phase.A weighted 2-norm regarding MA and MSD is significantly selected as the objective function,and the corresponding parameter optimization problem is constrained and nonconvex.Consequently,the Levenberg-Marquardt algorithm is employed as the parameter tuning law to ensure the convergence stability,and a simple method is proposed that provides the precise estimation of the gradient and Hessian matrix of the objective function in the nonlinear control system.Moreover,a multi-parameter accelerated iterative algorithm is proposed to further accelerate the convergence rate.For the ultra-precision motion stage,the position-dependent dynamics and disturbances make it difficult to achieve the performance robustness.To suppress the unmolded position-dependent dynamics and disturbances,a novel data-driven variable-gain DSMC is proposed.The essence that DSMC consists of linear feedback control term,feedforward control term and nonlinear switching control term,is revealed.As a result,a new design idea is put forward for DSMC where the above three control terms are separately designed in sequence.On the basis of the foregoing research,concepts of “variable-gain” and “data-driven” are newly introduced into DSMC.Therefore,the dependence on the full-state information and the accuracy model are simultaneously eliminated,and the trade-off between the performance robustness and the chattering alleviation is well balanced.