Effect of Improved Tracking for Atomic Force Microscope on Piezo Nonlinear Behavior

Nanotechnology is an area of modern science which deals with the control of matter at dimensions of 100 nm or less. In recent years, of all the available microscopy techniques, atomic force microscopy (AFM) has proven to be extremely versatile as an investigative tool in this field. However the performance of AFM is significantly limited by the effects of hysteresis, creep, cross‐coupling, and vibration in its scanning unit, the piezoelectric tube scanner (PTS). This article presents the design and experimental implementation of a single‐input single‐output (SISO) model predictive control (MPC) scheme with a vibration compensator which is based on an identified model of the PTS. The proposed controller provides an AFM with the capability to achieve improved tracking and results in compensation of the nonlinear effects. The experimental results, which compare the tracking performances of the proposed controller for different reference signals, highlight the usefulness of the proposed control scheme.     

A Novel Application of Minimax LQG Control Technique for High‐speed Spiral Imaging

Over the last two decades, increasing the scanning speed of an atomic force microscopy (AFM) has been attempted either by applying novel controllers, using alternative scanning methods, or by modifying the hardware setup. This paper demonstrates, the first two approaches to achieve high‐speed AFM image scanning. A robust minimax linear quadratic Gaussian (LQG) controller is designed and spiral scanning is considered as an alternative scanning method rather than conventional raster scanning. The minimax LQG controller is designed based on an uncertain system model which is constructed by measuring the plant variations due to variations in sample mass and also modeling error between the measured and model frequency responses. This controller is also robust against uncertainties introduced as a result of variations of sample mass, spillover dynamics of the scanner at frequencies higher than the first resonance frequency of the scanner, and variation in plant transfer functions due to temperature and humidity. The designed controller is experimentally implemented on an AFM using a dSPACE ds‐1103 real‐time prototyping system and open‐loop and closed‐loop spiral imaging performances are evaluated. The proposed controller provides sufficient damping at the resonant modes to accurately track the sinusoidal reference signal and generate vibration free images. Also, creep, hysteresis, and cross‐coupling effects are significantly reduced. The experimental results show that the proposed scheme outperforms the open‐loop case and some other existing approaches.     

ROBUST TWO‐DEGREE‐OF‐FREEDOM CONTROL OF AN ATOMIC FORCE MICROSCOPE

The performance of an atomic force microscope (AFM) is improved substantially by utilizing modern model‐based control methods in comparison to a standard proportional‐integral (PI) controlled AFM system. We present the design and implementation of a two‐degree‐of‐freedom (2DOF)‐controller to accomplish topography measurements at high scan‐rates with reduced measurement error. An H_∞‐controller operates the AFM system in a closed loop while a model‐based feedforward controller tracks the scanner to the last recorded scan‐line. Experimental results compare the actual performance of the standard PI‐controlled AFM and the 2DOF controlled system. The new controller reduces the control error considerably and enables imaging at higher speeds and at weaker tip‐sample interaction forces.     

A Survey of Methods Used to Control Piezoelectric Tube Scanners in High‐Speed AFM Imaging

In most nanotechnology applications, speed and precision are important requirements for obtaining good topographical maps of material surfaces using atomic force microscopes (AFMs), many of which use piezoelectric tube scanners (PTSs) for scanning and positioning at nanometric resolutions. For control engineers, the PTS is particularly interesting since its ability to enable the AFM to undertake 3D imaging is entirely dependent upon the use of a feedback loop. However, it suffers from various intrinsic problems that degrade its positioning performance, such as: (i) lightly damped low‐frequency resonant modes due to its mechanical structure; (ii) nonlinear behavior due to hysteresis and creep; (iii) the cross‐coupling effect between its axes (in 3D positioning systems such as AFMs); and (iv) effect of thermal drift. This article presents a survey of the literature on the PTS, an overview of a few existing innovative solutions for its nanopositioning and future research directions. This article will help the reader to walk around the present development of the PTS aimed at meeting the requirements for high‐speed AFM imaging.     

适用于原子力显微镜先进扫描模式的学习控制系统

原子力显微镜(AFM)是进行纳米测量和操作的一种重要工具.针对原子力显微镜系统,论文提出了一种基于学习控制的先进扫描模式.具体而言,首先构造了一种适用于AFM的学习控制系统,它由对于扫描管动态特性的最优逆补偿环节和对于样品表面特性的学习算法两部分组成.然后,针对测量过程中扫描线之间的偏移,通过将常见的比例-积分控制算法与这种学习控制相结合,实现了一种基于学习算法的先进扫描模式.论文将这种模式应用于周期性样品来测试其性能,仿真和实验结果表明它可以显著提高测量的速度和精度,同时将样品与探针针尖的距离控制在一个合理的范围之内,以避免损坏样品或探针.这种先进扫描模式可以应用于对快速生物过程的实时监测,同时也可以用来完成重复刻写等纳米操作.     

原子力显微镜系统广义预测控制与成像

在原子力显微镜(atomic force microscope,AFM)扫描样品时,控制参数调节困难,依赖于操作经验.本文基于在线动态模型辨识,提出了一种AFM系统广义预测自校正控制与成像方法.首先,利用CARIMA(controlled autoregressive and moving-average)参数模型来描述局部线性化后的AFM系统模型,并通过在线动态模型辨识得到线性化模型的参数;基于该模型,采用基于GPC(generalized predictive control)的优化方法,在线求解类PI(proportional integral)控制器的参数,进而得到一种具有控制参数自动调整功能的AFM成像方法.为了验证本文方法的有效性,进行了仿真与实验测试.结果表明,在AFM扫描速度不同或PI参数选择不恰当的情况下,该方法能够自动地调整控制器参数,从而减小控制误差,提高成像精度.     

Hysteresis Compensation and Adaptive Controller Design for a Piezoceramic Actuator System in Atomic Force Microscopy

This paper presents an indirect adaptive controller combined with hysteresis compensation to achieve high accuracy positioning control of piezoceramic actuators and illustrates the results with an atomic force microscope (AFM) application. A dynamic model of a piezoceramic actuator system in AFM is derived and analyzed. A feedforward controller based on the Preisach model is proposed to compensate for the nonlinear hysteresis effects. Then an indirect adaptive controller is designed to achieve desired tracking performance as well as deal with the uncompensated nonlinearity from hysteresis and the system parameter variation due to creep. Experimental results indicate that the proposed controller can significantly improve the positioning control accuracy of the piezoceramic actuator as well as achieve high image quality of the AFM system. The maximum scanning error was reduced from 2µm to 0.3µm in comparison with a proportional‐integral‐derivative (PID) controller. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

一种基于临近点集数据融合的AFM动态成像方法

原子力显微镜(Atomic force microscopy, AFM)是纳米技术和纳米操作领域中最重要的研究工具之一. 本文针对扫描成像的原子力显微镜, 提出了一种改进的AFM动态成像方法, 该方法分析了AFM系统中样品与针尖之间的非线性力对成像精度的影响, 通过对扫描过程中获得的成像数据进行融合滤波, 有效地提高了快速AFM的成像精度. 具体而言, 论文首先分析了原子力显微镜当前成像方法存在的主要问题, 然后针对在高速扫描或者样品形貌高度有突变时, 因AFM系统中非线性因素而引起的成像误差, 提出了一种基于临近点集数据融合的改进动态成像方法, 以提高AFM对于样品表面形貌的成像精度. 最后分别利用原子力显微镜仿真平台数据和实验数据, 验证了本文提出的改进成像方法的性能.     

High speed laser scanning microscopy by iterative learning control of a galvanometer scanner

Iterative learning control (ILC) for a galvanometer scanner is proposed to achieve high speed, linear, and accurate bidirectional scanning for scanning laser microscopy. A galvanometer scanner, as a low stiffness actuator, is first stabilized with a feedback control compensating for disturbances and nonlinearities at low frequencies, and ILC is applied for the control of the fast scanning motion. For stable inversion of the non-minimum phase zeros, a time delay approximation and a zero phase approximation are used for design of ILC, and their attainable bandwidths are analyzed. Experimental results verify the benefits of ILC of its wide control bandwidth, enabling a faster, more linear, and more accurate scanning without a phase lag and a gain mismatch. At the scan rate of 4112 lines per second, the root mean square (RMS) error of the ILC can be reduced by a factor of 73 in comparison with the feedback controlled galvanometer scanner of the commercial system.     

Electromagnetic Two-Dimensional Scanner Using Radial Magnetic Field

In this paper, we present the design, fabrication, and measurement results of a two-dimensional electromagnetic scanning micromirror actuated by radial magnetic field. The scanner is realized by combining a gimbaled single-crystal-silicon micromirror with a single turn electroplated metal coil, with a concentric permanent magnet assembly composed of two concentric permanent magnets and an iron yoke. The proposed scanner utilizes the radial magnetic field rather than using a lateral magnetic field oriented 45deg to the horizontal and vertical scan axes to achieve a biaxial magnetic actuation. The single turn coil fabricated with electroplated copper achieves a nominal resistance of 1.2 Omega. A two-dimensional scanner with mirror size of 1.5 mm in diameter was fabricated. Maximum optical scan angle of 8.8deg in horizontal direction and 8.3deg in vertical direction were achieved. Forced actuation of the gimbal at 60 Hz and resonant actuation of the micromirror at 19.1-19.7 kHz provide slow vertical scan and fast horizontal scan, respectively. The proposed scanner can be used in raster scanning laser display systems and other scanner applications.     

Design of a novel adaptive TSK-fuzzy speed controller for use in direct torque control induction motor drives

This study proposes an adaptive Takagi-Sugeno-Kang-fuzzy (TSK-fuzzy) speed controller (ATFSC) for use in direct torque control (DTC) induction motor (IM) drives to improve their dynamic responses. The proposed controller consists of the TSK-fuzzy controller, which is used to approximate an ideal control law, and a compensated controller, which is constructed to compensate for the difference between the TSK-fuzzy controller and the ideal control law. Parameter variations and external load disturbances were considered during the design phase to ensure the robustness of the proposed scheme. The parameters of the TSK-fuzzy controller were adjusted online based on the adaptive rules derived in Lyapunov stability theory. The ATFSC, fuzzy control, and PI control schemes were experimentally investigated, using the root mean square error (RMSE) performance index to evaluate each scheme. The robustness of the proposed ATFSC was verified using simulations and experiments, which involved varying parameters and external load disturbances. The experimental results indicate that the ATFSC scheme outperformed the other control schemes.     

面向ADHD的利用HTC Vive采集手部运动数据的可行性研究

虚拟现实技术在辅助注意力缺陷伴多动障碍(ADHD)的客观诊断中取得了一定成效;为了分析ADHD患者与正常儿童在虚拟环境中手部交互的运动差异,需要追踪被试的手部运动并对其进行测量;消费级虚拟现实系统HTC Vive配有手持控制器,具有运动捕捉功能;然而目前临床上还未将手持控制器用于人体手部运动追踪,因此尝试探讨手持控制器用于追踪人体手部运动的可行性,并设计了两个实验;实验一评估HTC Vive系统追踪手持控制器静置时的位置和旋转精度,分析系统的随机误差;实验二评估系统追踪手持控制器的平移和旋转精度;实验一测量得出:手持控制器静置时在X、Y、Z轴的位置抖动误差均小于0.25 mm,旋转抖动误差均小于0.05°;进而采用艾伦方差方法对实测数据进行分析,得到系统量化噪声、零偏不稳定性、速率斜坡等主要误差项系数;实验二测量得出:手持控制器绕X、Y、Z轴的旋转误差均小于0.35°,沿X、Y、Z轴的平移误差均小于3 mm;实验结果表明:HTC Vive系统可用于采集人体的手部运动数据,为辅助ADHD患者的客观诊断提供了可靠的基础支持。     

积分加纯滞后系统的双预测PI控制及其应用

Smith预估控制器控制积分加大纯滞后过程时,鲁棒稳定性差,输出存在静态余差,无实际应用价值.提出了一类基于该过程的双预测PI控制器:具有内环和外环两种预测PI控制器.内环将系统稳定,外环消除输入干扰的影响和改善控制系统的动态性能.这种控制器结构简单,可调参数少,参数的调节方便、直观.仿真和实际应用表明:在干扰和模型失配的情况下,此类控制器仍然具有良好的控制性能和鲁棒稳定性能,是一种值得在实际工程中推广应用的新型控制器.     

Closed-loop analysis and control of a non-inverting buck–boost converter

In this article, a cascade controller is designed and analysed for a non-inverting buck–boost converter. The fast inner current loop uses sliding mode control. The slow outer voltage loop uses the proportional–integral (PI) control. Stability analysis and selection of PI gains are based on the nonlinear closed-loop error dynamics incorporating both the inner and outer loop controllers. The closed-loop system is proven to have a nonminimum phase structure. The voltage transient due to step changes of input voltage or resistance is predictable. The operating range of the reference voltage is discussed. The controller is validated by a simulation circuit. The simulation results show that the reference output voltage is well-tracked under system uncertainties or disturbances, confirming the validity of the proposed controller.     

Cantilever probes for high speed AFM

Since the invention in 1986 atomic force microscopy (AFM) has become the most widely used scanning probe microscopy (Binnig et al. in Phys Rev Lett 56:930–933, 1986). The microscope images the interaction of forces like Van der Waals or Coulomb forces between a sample and the apex of a small tip integrated near the free end of a flexible cantilever. But as all other scanning probe techniques the AFM requires serial data acquisition and suffers therefore from a low temporal resolution. Enhancing the speed to video rate imaging makes high demands on scanner technology, control electronics and on the key feature the cantilever with integrated sharp stylus. For the cantilever probes, fundamental resonance frequencies in the MHz regime are envisaged while the force constant of a few nN/nm shall be maintained. We present different novel AFM probes with ultrashort cantilevers and integrated sharp tips for high speed AFM while focusing on widely dispersed applications and on aspects of mass fabrication.     

Wavelet neural adaptive proportional plus conventional integral-derivative controller design of SSSC for transient stability improvement

Although the PI or PID (PI/PID) controllers have many advantages, their control performance may be degraded when the controlled object is highly nonlinear and uncertain; the main problem is related to static nature of fixed-gain PI/PID controllers. This work aims to propose a wavelet neural adaptive proportional plus conventional integral-derivative (WNAP+ID) controller to solve the PI/PID controller problems. To create an adaptive nature for PI/PID controller and for online processing of the error signal, this work subtly employs a one to one offline trained self-recurrent wavelet neural network as a processing unit (SRWNN-PU) in series connection with the fixed-proportional gain of conventional PI/PID controller. Offline training of the SRWNN-PU can be performed with any virtual training samples, independent of plant data, and it is thus possible to use a generalized SRWNN-PU for any systems. Employing a SRWNN-identifier (SRWNNI), the SRWNN-PU parameters are then updated online to process the error signal and minimize a control cost function in real-time operation. Although the proposed WNAP+ID is not limited to power system applications, it is used as supplementary damping controller of static synchronous series compensator (SSSC) of two SSSC-aided power systems to enhance the transient stability. The nonlinear time-domain simulation and system performance characteristics in terms of ITAE revealed that the WNAP+ID has more control proficiency in comparison to PID controller. As additional simulations, the features of the proposed controller are compared to those of the literature while some of its promising features like its fast noise-rejection ability and its high online adapting ability are also highlighted.     

Real Time Implementation of Fuzzy Gain Scheduling of PI Controller for Induction Motor Machine Control

In this work the control of an induction motor using fuzzy gain scheduling of PI controller (adaptive FLC-PI) is presented. Fuzzy rules are utilized on-line to determine the controller parameters based on tracking error and its first time derivative. Simulation and experimental results of the proposed scheme show good performances compared to the PI controller with fixed parameters.     

Synthesis of reinforcement learning,neural networks and PI control applied to a simulated heating coil

An accurate simulation of a heating coil is used to compare the performance of a proportional plus integral (PI) controller to the following schemes for learning improved control: a neural network trained to predict the steady-state output of the PI controller, a neutral network trained to minimize the n-step ahead error between the coil output and the set point, and a reinforcement learning agent trained to minimize the sum of the squared error over time. Although the PI controller works very well for this task, the neural networks showed improved performance. The reinforcement learning agent, when combined with a PI controller, learned to augment the PI control output for the subset of states for which control can be improved.     

Design of a Robust Optimal Decentralized PI Controller Based on Nonlinear Constraint Optimization For Level Regulation: An Experimental Study

This paper presents the development of a new robust optimal decentralized PI controller based on nonlinear optimization for liquid level control in a coupled tank system. The proposed controller maximizes the closed-loop bandwidth for specified gain and phase margins, with constraints on the overshoot ratio to achieve both closed-loop performance and robustness. In the proposed work, a frequency response fitting model reduction technique is initially employed to obtain a first order plus dead time (FOPDT) model of each higher order subsystem. Furthermore, based on the reduced order model, a proposed controller is designed. The stability and performance of the proposed controller are verified by considering multiplicative input and output uncertainties. The performance of the proposed optimal robust decentralized control scheme has been compared with that of a decentralized PI controller. The proposed controller is implemented in real-time on a coupled tank system. From the obtained results, it is shown that the proposed optimal decentralized PI controller exhibits superior control performance to maintain the desired level, for both the nominal as well as the perturbed case as compared to a decentralized PI controller.      

Tuning and analysis of a fuzzy PI controller based on gain andphase margins

The nonlinearity of the simplest fuzzy PI controller with different inference methods has been discussed and it shows that Mamdani's minimum inference method is the most general inference method for the fuzzy PI controller. In addition, a novel tuning method based on gain and phase margins has been proposed to determine the weighting coefficients of the fuzzy PI controllers. With the proposed tuning formula, the nature of the fuzzy PI controller has been analyzed and it shows the desired characteristics in terms of gain and phase margins when controlling linear plants. Numerical simulations are presented to show the validity of the proposed tuning method