Iterative Parameter Optimization for Multiple Switching Control Applied to a Precision Stage for Microfabrication

This paper proposes an iteration procedure to derive optimal parameters for a multiple switching control architecture. Control design is usually a compromise between various performance requirements; therefore, switching between multiple controllers that achieve a particular performance under different conditions can potentially improve the overall system behavior. In this paper, we consider a control-switching mechanism that can automatically switch controllers based on the prediction of future responses, and we develop an iteration procedure that can optimize the mechanism parameters, such as the number of controllers and the prediction horizon. We then implement the proposed mechanism in a long-stroke precision stage, and demonstrate the effectiveness of switching robust control with simulations and experiments. Lastly, we integrate the stage with a two-photon polymerization system to fabricate microlenses. The optical properties confirm that the proposed iterative parameter optimization procedure is effective in improving the performance of microfabrication employing multiple switching control.

[1]  Fu-Cheng Wang,et al.  Development of a dual-stage and visual-servo filming robot , 2021, J. Syst. Control. Eng..

[2]  Fu-Cheng Wang,et al.  Precision positioning control of a long-stroke stage employing multiple switching control , 2020 .

[3]  T. Georgiou,et al.  Optimal robustness in the gap metric , 1989, Proceedings of the 28th IEEE Conference on Decision and Control,.

[4]  Mahmud Iwan Solihin,et al.  Fuzzy-tuned PID Anti-swing Control of Automatic Gantry Crane , 2010 .

[5]  Xianmin Zhang,et al.  Nonlinear Hysteresis Modeling of Piezoelectric Actuators Using a Generalized Bouc–Wen Model , 2019, Micromachines.

[6]  Fu-Cheng Wang,et al.  Study on the transient response to the point-to-point motion controls on a dual-axes air-bearing planar stage , 2020 .

[7]  Amir M. Sodagar,et al.  Combined PID and LQR controller using optimized fuzzy rules , 2019, Soft Comput..

[8]  Wilson J. Rugh,et al.  Gain scheduling for H-infinity controllers: a flight control example , 1993, IEEE Trans. Control. Syst. Technol..

[9]  K. Glover,et al.  Robust stabilization of normalized coprime factor plant descriptions with H/sub infinity /-bounded uncertainty , 1989 .

[10]  Yuxiao Qin,et al.  A Fuzzy Adaptive PID Controller Design for Fuel Cell Power Plant , 2018, Sustainability.

[11]  Keith Glover,et al.  A loop-shaping design procedure using H/sub infinity / synthesis , 1992 .

[12]  Ali Khaki Sedigh,et al.  Design of a Switching PID Controller for a Magnetically Actuated Mass Spring Damper , 2020 .

[13]  Yudong Zhang,et al.  IMAGE-BASED HYSTERESIS MODELING AND COMPENSATION FOR AN AFM PIEZO-SCANNER , 2009 .

[14]  Wei Zhu,et al.  Hysteresis modeling and displacement control of piezoelectric actuators with the frequency-dependent behavior using a generalized Bouc–Wen model , 2016 .

[15]  Md. Alamgir Hossain,et al.  Comparative Analysis among Single-Stage, Dual-Stage, and Triple-Stage Actuator Systems Applied to a Hard Disk Drive Servo System , 2019, Actuators.

[16]  Zhili Long,et al.  A Compound Control Based on the Piezo-Actuated Stage with Bouc–Wen Model , 2019, Micromachines.

[17]  Jianmin Yang,et al.  A fuzzy rule-based PID controller for dynamic positioning of vessels in variable environmental disturbances , 2020 .

[18]  Ian R. Petersen,et al.  MPC in high-speed atomic force microscopy , 2016, 2016 Australian Control Conference (AuCC).

[19]  Analysis of the Vibration Suppression of Double-Beam System via Nonlinear Switching Piezoelectric Network , 2021 .

[20]  Fu-Cheng Wang,et al.  The Development and Control of a Long-Stroke Precision Stage , 2017 .

[21]  Yongchun Fang,et al.  Improved direct inverse tracking control of a piezoelectric tube scanner for high-speed AFM imaging☆ , 2015 .

[22]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[23]  Hiromu Hirai,et al.  Mode switching control design with initial value compensation and its application to head positioning control on magnetic disk drives , 1996, IEEE Trans. Ind. Electron..

[24]  Fu-Cheng Wang,et al.  Micro-lens fabrication by a long-stroke precision stage with switching control based on model response prediction , 2019, Microsystem Technologies.