Huang Chengsi, Li Hongcheng
School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China.
Micromachines (Basel). 2021 Dec 8;12(12):1525. doi: 10.3390/mi12121525.
Due to the excellent advantages of high speed, high precision, and driving force, piezoelectric actuators nanopositioning systems have been widely used in various micro/nanomachining fields. However, the inherent resonance dynamic of the nanopositioning system generated by the flexure-hinge greatly deteriorates the positioning performance and limits the closed-loop bandwidth. Even worse, the notch filter for eliminating the effect of resonance does not work due to the varying resonant frequency resulting from the external disturbance or mass load. To this end, an adaptive notch filter for piezo-actuated nanopositioning system via position and online estimate dual-mode (POEDM) has been proposed in this paper, which can estimate the varying resonant frequency in real-time and suppress the resonance to improve the closed-loop bandwidth. First, a novel variable forgetting factor recursive least squares (VFF-RLS) algorithm for estimating resonant frequency online is presented, which is robust to the noise and provides the performances of both fast tracking and stability. Then, a POEDM method is proposed to achieve the online identification of the resonant frequency in the presence of noise and disturbance. Finally, a series of validation simulations are carried out, and the results indicate that, the frequency of input signal and the bandwidth have been achieved up to 12.5% and 87.5% of the first resonant frequency, respectively.
由于具有高速、高精度和驱动力等优异优点,压电致动器纳米定位系统已广泛应用于各种微纳加工领域。然而,由柔性铰链产生的纳米定位系统固有的共振动态特性极大地恶化了定位性能并限制了闭环带宽。更糟糕的是,由于外部干扰或质量负载导致共振频率变化,用于消除共振影响的陷波滤波器不起作用。为此,本文提出了一种通过位置和在线估计双模(POEDM)的压电驱动纳米定位系统自适应陷波滤波器,它可以实时估计变化的共振频率并抑制共振以提高闭环带宽。首先,提出了一种用于在线估计共振频率的新型可变遗忘因子递归最小二乘(VFF-RLS)算法,该算法对噪声具有鲁棒性,并提供快速跟踪和稳定性的性能。然后,提出了一种POEDM方法,以在存在噪声和干扰的情况下实现共振频率的在线识别。最后,进行了一系列验证仿真,结果表明,输入信号的频率和带宽分别达到了第一共振频率的12.5%和87.5%。