Nanopositioning System Research Articles

Piecewise modified Prandtl-Ishlinskii model for precise nano-positioning

Piezoelectric ceramic, an indispensable micro-nano actuator, has advantages of small size, high sensitivity and strong controllability, which is widely applied in various fields like micro-nano processing, medicine, chemistry and materials. However, its nonlinear and asymmetric hysteresis features directly affect its positioning accuracy. The classical and generalized Prandtl-Ishlinskii models with linear symmetry operators are commonly used to deal with these issues, but they still face difficulties in asymmetric systems. Therefore, a piecewise modified Prandtl-Ishlinskii (PMPI) model is proposed to compensate nonlinear and asymmetric hysteresis in this paper. The new nonlinear operator and piecewise nonlinear envelope function are introduced into the PMPI model. Independent right and left parts are adopted to describe hysteresis increasing and decreasing stages, while the threshold and weight vectors correspond to them. Weight vectors are extended and a new diagonal matrix is constructed for avoiding excessive parameters and computation. Simulations and experiments are shown that the PMPI model has good compensation performance and effectiveness, which has better fitting, higher accuracy, fewer parameters and computation, and can be well applied to the precise nano-positioning systems with less nonlinear and asymmetric errors.

Research on Micro-/Nano-Positioning System Driven by a Stepper Motor

To achieve cost-effective micro-/nano-displacement adjustment, this paper integrates the advantages of flexible hinge micro-/nano-displacement transmission. A linear stepper motor is utilized as the driving component to design and develop a high-precision, low-cost micro-/nano-positioning system. The structure, design, and working principles of the micro-/nano-positioning platform are introduced. The scaling factor model between micro-positioning platforms and nano-positioning platforms is analyzed. Static and dynamic models of flexible mechanisms have been established. The dimensions of the mechanical structure and the selection of motors are determined. The mechanical characteristics of the micro-/nano-positioning platform are validated through finite element analysis. To address the characteristic of increasing loads during the transmission process, an intelligent control system based on current feedback is designed and developed. The integration of drive and control provides a high level of system integration. Finally, experimental calibration was conducted to test the motion characteristics of the linear stepper motor-driven micro-/nano-positioning platform. It achieved a minimum displacement control resolution of 100 nm and demonstrated a certain level of stability.

Development of a novel monolithic compliant Lorentz-force-driven XY nanopositioning system

A novel monolithic compliant Lorentz-force-driven XY nanopositioning system (MCLNS) is designed, analyzed, and experimentally assessed with the aim of high-resolution positioning across a large workspace. A double-symmetric Lorentz-force actuator (DSLA) with the benefits of zero friction, high thrust, and large stroke is proposed to generate the actuation force. Correspondingly, a monolithic four-prismatic parallel compliant mechanism (4P-PCM) is exploited to transmit the actuation motion to the central platform and minimize the parasitic motion. The unique integration of four DSLAs and one 4P-PCM make the proposed MCLNS possess compact structure and stable performance. The characterization of the MCLNS is formulated by a specially established analytical model and validated by finite-element analysis simulation and experimental tests. Experimental studies show that the workspace of the MCLNS prototype is large than 0.87 × 0.87 mm2 and the positioning resolution of the MCLNS prototype is better than 9 nm. By means of a nonlinear forward proportional integral derivative control strategy, the maximum contouring error of the MCLNS is maintained within 2.7% while tracking a 1257 μm s−1 circular trajectory.

A Hybrid Add-on Damping Strategy for Self-Stabilization Nanopositioning System With High-Static-Low-Dynamic Stiffness Property

A Hybrid Add-on Damping Strategy for Self-Stabilization Nanopositioning System With High-Static-Low-Dynamic Stiffness Property

A nano-positioning system based on an optimal two-stage linear displacement amplifier

Nano-positioning systems with large motion ranges often employ displacement amplifiers with poor linearity and a large footprint. Here, we propose a compact nano-positioning system comprising an optimally designed two-stage displacement amplifier with linear input-output relationship over a large motion range. The first stage is a truncated bridge amplifier whose size is 25% of a conventional bridge amplifier, while the second stage is a modified lever-type displacement amplifier whose amplified motion direction can be chosen as desired. It is proposed to exploit the compliance of the structure to improve its linearity by operating the truncated bridge amplifier at a specific optimal angle. A simple reduced-order model is proposed and is shown to agree with finite element analysis to within 1%. Further, the variation in the amplification ratio at various payloads are analysed as function of input displacement. Subsequently, a two-stage amplifier with amplification 28 demonstrating a linear range of 940 µm is fabricated using acrylic. This amplifier’s nonlinearity is less than 5.2%, representing about 10-fold improvement compared to a conventional bridge amplifier. Lastly, a nano-positioner employing an optimal amplifier is fabricated using spring steel and demonstrated to possess nonlinearity less than 1.5% over a range of 360 µm and a natural frequency of 210 Hz with a footprint of 21 cm2, which represents a substantial improvement in range-to-footprint ratio compared to other amplifiers of similar natural frequencies.

Precision Motion Control of a Piezoelectric Actuator via a Modified Preisach Hysteresis Model and Two-Degree-of-Freedom H-Infinity Robust Control.

The nonlinear hysteresis phenomenon can occur in piezoelectric-driven nanopositioning systems and can lead to reduced positioning accuracy or result in a serious deterioration of motion control. The Preisach method is widely used for hysteresis modeling; however, for the modeling of rate-dependent hysteresis, where the output displacement of the piezoelectric actuator depends on the amplitude and frequency of the input reference signal, the desired accuracy cannot be achieved with the classical Preisach method. In this paper, the Preisach model is improved using least-squares support vector machines (LSSVMs) to deal with the rate-dependent properties. The control part is then designed and consists of an inverse Preisach model to compensate for the hysteresis nonlinearity and a two-degree-of-freedom (2-DOF) H-infinity feedback controller to enhance the overall tracking performance with robustness. The main idea of the proposed 2-DOF H-infinity feedback controller is to find two optimal controllers that properly shape the closed-loop sensitivity functions by imposing some templates in terms of weighting functions in order to achieve the desired tracking performance with robustness. The achieved results with the suggested control strategy show that both hysteresis modeling accuracy and tracking performance are significantly improved with average root-mean-square error (RMSE) values of 0.0107 μm and 0.0212 μm, respectively. In addition, the suggested methodology can achieve better performance than comparative methods in terms of generalization and precision.

Bouc-Wen model with machine learning for SISO and MIMO nano-positioning system

Most of the application in present world have taken ‘Nano’ as a part of their near future implementation. In Nano-Positioning System (NPS) mechanical dynamics are handled at Nano scale. Designing a precision NPS is a greater challenge. Modified linearized Bouc-Wen(BW) model gives the better hysteresis, static and dynamic behavior. In this work SISO (Sıngle-input Sıngle-Output) and MIMO (Multiple-Input Multiple-Output) models of NPS are designed. Previously, system was basically designed to handle conventional macro level dynamics and the same has been extended to handle Nano scale in this work. Kalman Filtering is included to achieve very sustainable results in NPS. The NPS is designed in MATLAB/Simulink with 3 types of electrical signals. Each design is compared using various performance parameters. Machine learning process is included to suggest the appropriate input voltage level sui to obtain desired displacement.

Robust Adaptive Tracking Control of a 3D Vertical Motion System for Nanometer Precision Applications

In this paper we address the modeling and tracking control problem of an overactuated lift and tilt vertical nanopositioning system. We derive a model based on the rigid body dynamics which adequately describes the first resonance mode of each motion axis. This model is validated with measured data in the frequency domain to illustrate that it adequately reflects the real behavior. We further device an abstract model for the derivation of advanced control strategies. By virtue of the single axis model, three SISO controllers are implemented. The control strategy is accomplished comprising a nominal feedforward and LQG-type controller plus an L1 adaptive augmentation with output feedback. The baseline (or nominal) controller features sufficiently high bandwidth for the mere stabilization, decoupling, and disturbance rejection, while the L1 adaptive component plays a central role for recovering the nominal closed-loop dynamics in the presence of parametric uncertainties w.r.t. the input gain which are quite difficult to handle in the nominal design. The effectiveness and robustness of the proposed control strategy is verified via real-time experiments featuring subnanometer and nanoradian tracking errors which seem to be fully-dominated by the measurement noise.

Design of the nanopositioning and mechanical system for cavity-based X-ray free electron laser

With forming of an X-ray cavity with a set of narrow bandwidth diamond Bragg crystals and by storing and recirculating the output of an amplifier in an X- ray cavity so that the X-ray pulse can interact with following fresh electron bunches over many passes thus enabling the development of full temporal coherence, we will be able to build cavity-based X-ray FELs (CBXFELs) such as the X-ray free-electron laser oscillator (XFELO) and the X-ray regenerative amplifier free-electron laser (XRAFEL) [1, 2]. One of the key challenges to forming the X-ray cavity is the nanopositioning design and construction of the cavity mechanical system. In this paper, we present the design of the nanopositioning and mechanical system that is currently under construction for use in a proof-of-principle cavity-based X-ray free electron laser experiment at the LCLS-II at SLAC.

A Digital Observer-Based Repetitive Learning Composite Control Method for Large Range Piezo-Driven Nanopositioning Systems

In this study, a novel digital compound compensation method is proposed to compensate for the hysteresis nonlinearity and the drift disturbance of a piezoelectric nanopositioning system with a large range. The overall hysteresis behaviors can be divided into the static amplitude-dependent behavior and the dynamic rate-dependent behavior, where the static hysteresis is compensated for by a novel discrete feedforward controller, while the dynamic hysteresis and the drift disturbance are compensated for by a novel discrete composite feedback controller composed of a drift observer-based state feedback controller and a repetitive learning controller. Compared with traditional control strategies, the proposed compound control strategy, including feedforward and feedback components, can eliminate system errors more effectively when tracking large range signals with obvious hysteresis. Moreover, the proposed online drift observer is superior over a traditional offline drift compensator both in response speed and compensation accuracy. Sufficient simulation tests and convincing tracking experiments, with large range periodic signals up to 90 μm, are carried out. And comparisons with the two classical control algorithms are performed. The tracking results show that the mean absolute error of the proposed control method is minor compared with the other two algorithms, which validates that the proposed strategy can efficiently compensate for the hysteresis nonlinearity and the drift disturbance.

Robust Tracking Control of Piezo-Actuated Nanopositioning Stage Using Improved Inverse LSSVM Hysteresis Model and RST Controller

Nanopositioning technology is widely used in high-resolution applications. It often uses piezoelectric actuators due to their superior characteristics. However, piezoelectric actuators exhibit a hysteresis phenomenon that limits their positioning accuracy. To compensate for the hysteresis effect, developing an accurate hysteresis model of piezoelectric actuators is very important. This task is challenging, requiring some considerations of the multivalued mapping of hysteresis loops and the generalization capabilities of the model. This challenge can be dealt with by developing a machine learning-based model, whose inverse model can be used to efficiently design an accurate feedforward controller for hysteresis compensation. However, this approach depends on model accuracy and the type of data used to train the model. Thus, accurate prediction of the hysteresis behavior may not be guaranteed in the presence of disturbances. In this paper, a machine learning-based model is used to design a hysteresis compensator and then combined with a robust feedback controller to enhance the robustness of a nanopositioning control system. The proposed model is based on hysteresis operators, the least square support vector machine (LSSVM) method, and particle swarm optimization (PSO) algorithm. The inverse model is used to design the feedforward controller, and the RST controller is employed to develop feedback control. Our main contribution is the introduction of a hybrid controller capable of compensating for the hysteresis effect, and at the same time, eliminating remaining modeling errors and rejecting disturbances. The performance of the proposed approach is evaluated through MATLAB simulation, as well as through real-time experiments. The experimental results of our approach demonstrate superior tracking performance compared with the PID-LSSVM controller.

Application of Least-Squares Support-Vector Machine Based on Hysteresis Operators and Particle Swarm Optimization for Modeling and Control of Hysteresis in Piezoelectric Actuators

Nanopositioning systems driven by piezoelectric actuators are widely used in different fields. However, the hysteresis phenomenon is a major factor in reducing the positioning accuracy of piezoelectric actuators. This effect makes the task of accurate modeling and position control of piezoelectric actuators challenging. In this paper, the learning and generalization capabilities of the model are efficiently enhanced to describe and compensate for the rate-independent and rate-dependent hysteresis using a kernel-based learning method. The proposed model is inspired by the classical Preisach hysteresis model, in which a set of hysteresis operators is used to address the problem of mapping, and then least-squares support-vector machines (LSSVM) combined with a particle swarm optimization (PSO) algorithm are used for identification. Two control schemes are proposed for hysteresis compensation, and their performance is evaluated through real-time experiments on a nanopositioning platform. First, an inverse model-based feedforward controller is designed based on the LSSVM model, and then a combined feedback/feedforward control scheme is designed using a classical control strategy (PID) to further enhance the tracking performance. For performance evaluation, different datasets with a variety of hysteresis loops are used during the simulation and experimental procedures. The results show that the proposed method is successful in enhancing the generalization capabilities of LSSVM training and achieving the best tracking performance based on the combination of feedforward control and PID feedback control. The proposed control scheme outperformed the inverse Preisach model-based control scheme in terms of both positioning accuracy and execution time. The control scheme that uses the LSSVM based on nonlinear autoregressive exogenous (NARX) models has significantly less computational complexity compared to our control scheme but at the expense of accuracy.

Development and Testing of a Large-Stroke Nanopositioning Stage With Linear Active Disturbance Rejection Controller

Flexure-based scanning stages driven by piezoelectric (PZT) actuator with large stroke, nanoscale precision, and high bandwidth are quite appealing for developing an advanced multiphoton polymerization 3-D nanolithography system. The motivation of this article is to develop a nanopositioning system, which can simultaneously achieve large stroke, high bandwidth, and nanoscale precision to ensure its machining size, efficiency, and accuracy without traditional step-by-step splicing operations. First, an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">XY</i> nanopositioning stage with millimeter-scale workspace and nanoscale positioning accuracy is designed. Besides, the natural frequency modeling of the nanopositioning stage is conducted by resorting to compliance analysis based on the matrix method, which is validated by a finite-element analysis (FEA). Moreover, linear active disturbance rejection controller (LADRC) is demonstrated that it can be equivalent to a PID controller filtered using a second-order low-pass filter, which theoretically verifies the effectiveness of controlling the nanopositioning stage. In order to complete LADRC’s successful implementation for nanopositioning stage, a novel quantitative one-parameter-tuning method of LADRC is proposed. Finally, a series of trajectory tracking experiments has been carried out to verify the effectiveness and superiority of the proposed nanopositioning stage. The experimental results verify that the large-stroke compliant nanopositioning system has the capability to achieve millimeter stroke, which has reached 1.035 mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times \,\,1.035$ </tex-math></inline-formula> mm, while the average tracking error is kept within ±100 nm, and the closed-loop bandwidth is achieved up to 32 Hz. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —With the purpose to effectively improve the performance in terms of stroke, speed, and accuracy for the piezoelectric (PZT)-actuated scanning system, a completely decoupled nanopositioning stage with millimeter-scale travel range is developed and linear active disturbance rejection controller (LADRC) strategy with a novel quantitative one-parameter-tuning method of strategy is proposed. Experimental results indicate that the compliant nanopositioning system has the capability to achieve millimeter stroke, which has reached 1.035 mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times \,\,1.035$ </tex-math></inline-formula> mm, while the average tracking error of dynamic tracking control of the nanopositioning stage is kept within ±100 nm, and the closed-loop bandwidth is achieved up to 32 Hz. Therefore, the developed nanopositioning system has satisfactory performance for fulfilling advanced large-size multiphoton polymerization 3-D nanolithography task without step-by-step splicing operations. In summary, the potential applications of the proposed large-stroke nanopositioning strategy will be promising.

Development of a Parallel Dual-Stage Compliant Nanopositioning System

This paper presents a novel parallel dual-stage compliant nanopositioning system (PDCNS), aimed at nanoscale positioning for microscale manipulation. In the developed PDCNS, the coarse stage actuated by the voice coil motor and the fine stage driven by the piezoelectric actuator are integrated in a parallel manner by a specially devised A-shaped compliant mechanism, which leads to many excellent performances, such as good resolution and large stroke and broadband. To enhance the closed-loop-positioning capability of the proposed PDCNS, a double-servo cooperative control (DSCC) strategy is specially constructed. The performance of the proposed PDCNS is evaluated by analytical model, finite element analysis, and experimental research. Results show that the first-order resonance frequency of the designed A-shaped compliant mechanism can reach 99.7 Hz. Combined with the designed DSCC, the developed PDCNS prototype is demonstrated to provide a stroke of 1.49 mm and a positioning resolution of ≤50 nm.

Low-cost, open-source XYZ nanopositioner for high-precision analytical applications

Nanoscale positioning has numerous applications in both academia and industry. A growing number of applications require devices with long working distances and nanoscale resolutions. Friction–inertia piezoelectric positioners, which are based on the stick–slip mechanism, achieve both nanometer resolution and centimeter-scale travel. However, the requirements of complex preload mechanism, precision machining, and precise assembly increase the cost of conventional friction–inertia nanopositioners. Herein we present the design of an open-source XYZ-axis nanopositioning system. Utilizing a magnet-based stick–slip driving mechanism, the proposed XYZ nanopositioner provides several advantages, including sub-nanometer resolution, a payload capacity of up to 12 kg (horizontal), compact size, low cost, and easy assembly; furthermore, the system is adjustment-free. The performance tests validate the precision of the system in both scanning and stepping operation modes. Moreover, the resonant spectra affirm the rigidity and dynamic response of the mechanism. In addition, we demonstrate the practical applications of this nanopositioner in various measurement techniques, including scanning electron microscopy, vibrometry, and atomic force microscopy. Furthermore, we present 11 variations of the nanopositioner designs that are either compatible with ultra-high-vacuum systems and other existing systems, 3D printable, or hacking commercial linear slides.

Calculation of the modified control matrix for a selected unimorph deformable mirror to compensate the piezoelectric hysteresis effect using the inverse Bouc-Wen model.

The hysteresis behavior of piezoelectric actuators degrades the positioning accuracy and bandwidth of nano-positioning systems. Therefore, considering the hysteresis of piezoelectric deformable mirrors is completely essential and also improves the modeling accuracy of adaptive optics layouts. Because of the unique adaptability and mathematical flexibility of the Bouc-Wen model it has gained popularity, and as a result, in many scientific applications, it is one of the most conventional models typically employed to describe nonlinear hysteretic systems. Among different deformable mirrors, a unimorph piezoelectric deformable mirror is a suitable choice to be used in adaptive optics systems because of its relative convenience and cost-effective production. This paper proposes a new, to the best of our knowledge, approach to determine the influence function and the voltage control matrix of a specific unimorph mirror by considering a simplified inverse Bouc-Wen hysteresis model as a frequency function. Then the results for two selected standard Zernike modes, defocus and astigmatism-x, have been simulated using Comsol Multiphysics and MATLAB at a range of 5 to 100 Hz. For a more comprehensive comparison, the root-mean-square error and the coefficients of the Zernike terms have been applied as two criteria. According to the simulation results, the hysteresis effect of piezoelectric actuators has been significantly compensated by applying the inverse Bouc-Wen model at different frequencies, especially for higher frequencies. The effectiveness of the inverse Bouc-Wen model to compensate the hysteresis has been observed in astigmatism-x mode slightly more than in the defocus mode.

Convex Inner Approximation for Mixed $H_2$/$H_\infty$ Control With Application to a 2-DoF Flexure-Based Nanopositioning System

This article presents a convex inner approximation approach for mixed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${H}_2$</tex-math></inline-formula> / <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${H}_\infty$</tex-math></inline-formula> control of a flexure-based nanopositioning system. Generally for such positioning systems, the inevitable existence of model mismatch renders it often times difficult-to-achieve satisfying system performance. Additionally, it is essential to also note that the high-order resonances typically presented are prone to be activated if the controller is not designed appropriately, especially in the case when the control input variation arising from the design is unnecessarily drastic. Therefore, to circumvent the above undesirable possibilities, this work aims to improve the tracking performance with a suitable controller design that effectively suppresses the control input variation. Furthermore, despite the existence of model uncertainties, it is shown that it is possible for a subset of stabilizing controller gains to be characterized appropriately via convex inner approximation, which then further facilitates the determination of the controller by means of convex optimization. Rather importantly, this approach provides a performance guarantee with an optimized limiting bound to the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_2$</tex-math></inline-formula> -norm level (which assures optimal behavior for the system), and also concurrently limits the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_\infty$</tex-math></inline-formula> -norm level within a prescribed attenuation level (which satisfies a prescribed robustness measure). Finally, numerical optimization and comparative experiments are carried out for demonstrative purposes.

Rate-Dependent Modeling of Piezoelectric Actuators for Nano Manipulation Based on Fractional Hammerstein Model

Piezoelectric actuators (PEAs), as a smart material with excellent characteristics, are increasingly used in high-precision and high-speed nano-positioning systems. Different from the usual positioning control or fixed frequency tracking control, the more accurate rate-dependent PEA nonlinear model is needed in random signal dynamic tracking control systems such as active vibration control. In response to this problem, this paper proposes a Hammerstein model based on fractional order rate correlation. The improved Bouc-Wen model is used to describe the asymmetric hysteresis characteristics of PEA, and the fractional order model is used to describe the dynamic characteristics of PEA. The nonlinear rate-dependent hysteresis model can be used to accurately describe the dynamic characteristics of PEA. Compared with the integer order model or linear autoregressive model to describe the dynamic characteristics of the PEA Hammerstein model, the modeling accuracy is higher. Moreover, an artificial bee colony algorithm (DE-ABC) based on differential evolution was proposed to identify model parameters. By adding the mutation strategy and chaos search of the genetic algorithm into the previous ABC, the convergence speed of the algorithm is faster and the identification accuracy is higher, and the simultaneous identification of order and coefficient of the fractional model is realized. Finally, by comparing the simulation and experimental data of multiple sets of sinusoidal excitation with different frequencies, the effectiveness of the proposed modeling method and the accuracy and rapidity of the identification algorithm are verified. The results show that, in the wide frequency range of 1–100 Hz, the proposed method can obtain more accurate rate-correlation models than the Bouc-Wen model, the Hammerstein model based on integer order or the linear autoregressive model to describe dynamic characteristics. The maximum error (Max error) is 0.0915 μm, and the maximum mean square error (RMSE) is 0.0244.

Adaptive Notch Filter for Piezo-Actuated Nanopositioning System via Position and Online Estimate Dual-Mode.

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.

Design, fabrication and implementation of a high-performance compliant nanopositioner via 3D printing with continuous fiber-reinforced composite

Nanopositioning systems have been widely applied in scientific and emerging industrial applications. With simplicity in design and operation, flexure bearings with spatial constraints and voice coil based nano-actuators are considered in designing compliant compact nanopositioning systems. To achieve nano-metric positioning quality, monolithic fabrication of the positioner is preferred, which calls for 3D printing fabrication. However, conventional plastic material-based 3D printing suffers from low mechanical performances, and it is challenging to monolithically fabricate 3D compliant mechanisms with high mechanical performances. Here, we study the fabrication of continuous carbon fiber reinforced composites by 3D printing of the double parallelogram flexure beam structures for spatial constrained nanopositioner with enhanced vertical stiffness. Also, with the consideration of the beam structure design, the process parameters for embedding the carbon fibers are optimized to enhance the beam strengths. Experimental results demonstrate a significant performance improvement with the composite based nanopositioner in both stiffness and natural frequency, and its positioning resolution of 30 nm is achieved. The result of this study will serve as the building block to apply advanced 3D printing of composite structure for precision engineering in the presence of more complex spatial structures.