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Feasibility Study of Robust Neural Network Motion Tracking Control of Piezoelectric Actuation Systems for Micro/Nano Manipulation

机译:微/纳摩操纵压电致动系统鲁棒神经网络运动跟踪控制的可行性研究

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This paper presents a robust neural network motion tracking control methodology for piezoelectric actuation systems employed in micro/nano manipulation. This control methodology is proposed for tracking desired motion trajectories in the presence of unknown system parameters, non-linearities including the hysteresis effect, and external disturbances in the control systems. In this paper, the control methodology is established including the neural networks and a sliding scheme. In particular, the radial basis function neural networks are chosen in this study for function approximations. The stability of the closed-loop systems and convergence of the position and velocity tracking errors to zero are assured by the control methodology in the presence of the aforementioned conditions. Simulation results of the control methodology for tracking of a desired motion trajectory is presented. With the capability of motion tracking, the proposed control methodology can be utilised to realise high performance piezoelectric actuated micro/nano manipulation systems.
机译:本文介绍了微/纳米操纵中采用的压电致动系统的强大神经网络运动跟踪控制方法。该控制方法建议在存在未知的系统参数,非线性,包括滞后效应的非线性以及控制系统中的外部干扰的情况下跟踪所需的运动轨迹。在本文中,建立了控制方法,包括神经网络和滑动方案。特别地,在该研究中选择径向基函数神经网络,用于功能近似。通过在上述条件存在下,通过控制方法确保了闭环系统的稳定性和位置和速度跟踪误差为零的速度。介绍了跟踪所需运动轨迹的控制方法的仿真结果。利用运动跟踪的能力,可以利用所提出的控制方法来实现高性能压电驱动的微/纳米操纵系统。

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