English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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

Precise Motion Control of Wafer Stages via Adaptive Neural Network and Fractional-Order Super-Twisting Algorithm