Iterative Learning-based Model Predictive Control for Precise Trajectory Tracking of Piezo Nanopositioning Stage. - Shengwen Xie; Juan Ren (ACC, 2018)

Recurrent-neural-network-based Predictive Control of Piezo Actuators for Precision Trajectory Tracking. - Shengwen Xie; Juan Ren (ACC, 2019)

Predictive Control of Nano-positioning Stage Using Recurrent-neural-network-based Inversion Model. - Shengwen Xie; Juan Ren (CDC, 2019)

Discrete System Linearization using Koopman Operators for Predictive Control and Its Application in Nano-positioning. - Shengwen Xie; Juan Ren (AIM, 2020)

Towards Improving the Performance of the RNN-based Inversion Model in Output Tracking Control. - Shengwen Xie; Juan Ren (ACC, 2020)

Design of 2 μm Wavelength Polarization Mode Controllers. - Shengwen Xie; Sia M. L. Andersson; Shengwei Ye; Zhichuan Niu; John H. Marsh; Lianping Hou (UCET, 2020)

Linearization of Recurrent-Neural-Network- Based Models for Predictive Control of Nano-Positioning Systems Using Data-Driven Koopman Operators. - Shengwen Xie; Juan Ren (IEEE Access, 2020)

A Hybrid Position/Force Controller for Joint Robots. - Shengwen Xie; Juan Ren (ICRA, 2021)

Tracking Control Using Recurrent-Neural-Network-Based Inversion Model: A Case Study on a Piezo Actuator. - Shengwen Xie; Juan Ren (IEEE Trans. Ind. Electron., 2021)