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.

The continuous development of mini-LEDs has led to higher requirements for chip transfer technology, which makes it difficult for the intermittent transfer method with a mechanical ejector pin to meet these requirements. To solve this problem, a novel compliant 2-DOF ejector pin mechanism for the mass transfer of robotic mini-LED chips is proposed in this paper. The compliance matrix method and the Newton method are employed for system kinematic modeling and dynamics modeling, respectively. The static and dynamic analyses of the mechanism are carried out via ANSYS Workbench, and the results of FEA are demonstrated the effectiveness of theoretical calculation. Then, an ILC is utilized to control the device via a parameters regulation approach in the frequency domain. Finally, an open-loop test and a trajectory tracking test for the prototype are carried out verify the effectiveness of proposed device. The test results indicate that the working stroke of the mechanism reaches 120 μm, the natural frequency of the device is 250.85 Hz, the coupling rate is less than ±0.5% and the tracking errors of 10 Hz, 20 Hz and 30 Hz sinusoidal signals are all within ±1.5%. According to the results of theoretical analyses, FEA and test, it has been proved that the designed mechanism for the mass transfer of mini-LED chips is superiority and effective.

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Purpose Due to the advantages of fast response, high positioning precision and large stiffness, the piezoelectric-actuated nanopositioning stage is widely used in the micro/nanomachining fields. However, due to the inherent nonlinear hysteresis of the piezoelectric-actuator, the positioning accuracy of nanopositioning stage is greatly degraded. Besides, the nanopositioning stage is always performed with repetitive trajectories as the reference signals in applications, which makes the hysteresis behavior periodic. To this end, an adaptive resonance suppression iterative learning control (ARS-ILC) is proposed to address the hysteresis effect. With this effort, the positioning accuracy of the nanopositioning stage is improved. Design/methodology/approach The hysteresis behavior is identified by the Prandtl–Ishlinskii model. By establishing a convergence function, it is demonstrated that the learnable band of ILC is restricted by the lightly damping resonance of nanopositioning stage. Then, an adaptive notch filter (ANF) with constrained poles and zeros is adopted to suppress the resonant peak. Finally, online stability supervision (OSS) is used to ensure that the estimated frequency converges to the resonant frequency. Findings A series of experiments were carried out in the nanopositioning stage, and the results validated that the OSS is available to ensure the convergence of the ANF. Furthermore, the learnable band was extended via ARS-ILC; thus, the hysteresis behavior of nanopositioning stage has been canceled. Originality/value Due to high accuracy and easy implementation, the ARS-ILC can be used in not only nanopositioning stage control but other fabrication process control with repetitive motion.