An Dong, Li Ji, Li Songhua, Shao Meng, Wang Weinan, Wang Chuan, Yang Yixiao
School of Mechanical Engineering, Shenyang Jianzhu University, Shenyang 110168, China.
School of Microelectronics, Fudan University, Shanghai 200433, China.
Micromachines (Basel). 2023 Mar 27;14(4):742. doi: 10.3390/mi14040742.
Nanopositioning stages with piezoelectric actuators have been widely used in fields such as precision mechanical engineering, but the nonlinear start-up accuracy problem under open-loop control has still not been solved, and more errors will accumulate, especially under open-loop control. This paper first analyzes the causes of the starting errors from both the physical properties of materials and voltages: the starting errors are affected by the material properties of piezoelectric ceramics, and the magnitude of the voltage determines the magnitude of the starting errors. Then, this paper adopts an image-only model of the data separated by a Prandtl-Ishlinskii model (DSPI) based on the classical Prandtl-Ishlinskii model (CPI), which can improve the positioning accuracy of the nanopositioning platform after separating the data based on the start-up error characteristics. This model can improve the positioning accuracy of the nanopositioning platform while solving the problem of nonlinear start-up errors under open-loop control. Finally, the DSPI inverse model is used for the feedforward compensation control of the platform, and the experimental results show that the DSPI model can solve the nonlinear start-up error problem existing under open-loop control. The DSPI model not only has higher modeling accuracy than the CPI model but also has better performance in terms of compensation results. The DSPI model improves the localization accuracy by 99.427% compared to the CPI model. When compared with another improved model, the localization accuracy is improved by 92.763%.
带有压电致动器的纳米定位平台已在精密机械工程等领域得到广泛应用，但开环控制下的非线性启动精度问题仍未得到解决，且会累积更多误差，尤其是在开环控制下。本文首先从材料的物理特性和电压两方面分析了启动误差的成因：启动误差受压电陶瓷材料特性的影响，电压大小决定启动误差的大小。然后，本文基于经典的普朗特-伊什林斯基模型（CPI）采用了由普朗特-伊什林斯基模型（DSPI）分离数据的仅图像模型，该模型可根据启动误差特性分离数据后提高纳米定位平台的定位精度。该模型在解决开环控制下的非线性启动误差问题的同时，可提高纳米定位平台的定位精度。最后，将DSPI逆模型用于平台的前馈补偿控制，实验结果表明DSPI模型可解决开环控制下存在的非线性启动误差问题。DSPI模型不仅比CPI模型具有更高的建模精度，而且在补偿结果方面也具有更好的性能。与CPI模型相比，DSPI模型将定位精度提高了99.427%。与另一个改进模型相比，定位精度提高了92.763%。
