  To obtain precise motion control of wafer stages, an adaptive neural network
and fractional-order super-twisting control strategy is proposed. Based on
sliding mode control (SMC), the proposed controller aims to address two
challenges in SMC: 1) reducing the chattering phenomenon, and 2) attenuating
the influence of model uncertainties and disturbances. For the first challenge,
a fractional-order terminal sliding mode surface and a super-twisting algorithm
are integrated into the SMC design. To attenuate uncertainties and
disturbances, an add-on control structure based on the radial basis function
(RBF) neural network is introduced. Stability analysis of the closed-loop
control system is provided. Finally, experiments on a wafer stage testbed
system are conducted, which proves that the proposed controller can robustly
improve the tracking performance in the presence of uncertainties and
disturbances compared to conventional and previous controllers.
