適応ニューラルネットワークと分数階スーパーツイスティングアルゴリズムによるウェーハステージの精密運動制御
Precise Motion Control of Wafer Stages via Adaptive Neural Network and Fractional-Order Super-Twisting Algorithm
分数階ターミナル滑りモード面とスーパーツイスティングを組み合わせ、RBFニューラルネットで外乱・不確かさを補償するウェーハステージ向け制御手法を提案し、実験で追従性能の向上を示した。
著者: Zhian Kuang, Liting Sun, Huijun Gao, Masayoshi Tomizuka
分類: eess.SY, cs.RO, cs.SY
原文アブストラクト
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.
