压电陶瓷驱动器的复合控制方法研究

针对压电陶瓷驱动器中的迟滞非线性特性,提出一种提高压电陶瓷执行器定位精度的复合控制方法。建立了非等间隔阈值的Prandtl-Ishilinskii(PI)迟滞模型,通过自适应差分进化算法进行系统辨识,求取参数并建立逆模型。考虑到压电陶瓷迟滞非线性特性随输入信号频率变化的特点,采用融合PI逆模型前馈控制与滑模控制的复合控制方法用于压电陶瓷的精密驱动。实验结果表明,相比逆模型前馈和PID结合的复合控制方法,采用逆模型前馈和滑模复合控制方法,平均误差下降了0.0300μm,均方根误差下降了0.0346μm,能有效克服压电陶瓷迟滞非线性,提高系统跟踪性能。     

扫描隧道显微镜扫描器的迟滞非线性控制

压电驱动器被广泛应用于扫描隧道显微镜(scanning tunneling microscope,简称STM)的扫描器,但压电材料本身的迟滞非线性特性影响了STM的扫描精度。为了补偿由于迟滞非线性带来的扫描器控制误差,提高STM的扫描精度,基于迟滞非线性模型,设计了前馈控制器,并与PID反馈控制相结合。利用所设计的控制器进行了扫描实验,并与位移反馈控制扫描进行对比。实验结果表明,采用位移反馈控制时光栅周期相对测量误差和光栅线宽相对测量误差分别为4.41%和2.65%,采用迟滞逆模型与PID反馈的复合控制后,光栅周期相对测量误差和光栅线宽相对测量误差分别减小到1.26%和0.27%,迟滞引起的非线性误差得到了补偿,减小了扫描器控制误差,提高了扫描精度。     

叠堆式压电陶瓷驱动器的复合控制

提出了逆Bouc-Wen前馈控制与反馈控制相结合的复合控制算法,用于改善压电陶瓷驱动器对目标轨迹的跟踪性能。建立了压电陶瓷驱动器的Bouc-Wen迟滞动力学模型,并用粒子群算法(PSO)对该模型的参数进行识别。基于Bouc-Wen迟滞模型,提出了逆Bouc-Wen前馈补偿控制。最后,为消除迟滞模型的不确定性,引入比例积分(PI)反馈控制,并与前馈补偿控制构成复合控制算法。建立了基于dSPACE实时系统的压电陶瓷驱动实验平台,迟滞实验结果表明:压电陶瓷的迟滞误差量几乎为0,线性度高达96.5%;目标轨迹跟踪实验结果表明:复合控制算法的最大跟踪误差为0.180 5μm,均方根(RMS-Root mean square)跟踪误差为0.055 4μm,跟踪精度达到了10-8 m。相比于开环控制、前馈控制及PI反馈控制,提出的复合控制算法能够基本消除压电陶瓷的迟滞非线性,同时具有很好的轨迹跟踪性能。     

压电作动器的支持向量机迟滞模型

压电作动器被广泛应用于高精度定位领域,但是其固有的迟滞非线性会严重影响定位精度。为了准确地描述压电作动器的迟滞特性,提出了一种基于非线性自回归移动平均(NARMAX)的支持向量机(SVM)迟滞模型。为了建立SVM迟滞模型,首先需要将压电作动器的输入输出关系从一个多值映射问题转化为单值映射问题,对比了不同的单值映射对SVM迟滞模型精度及泛化能力的影响,提出了一种基于NARMAX构建单值映射的方法,建立了在全局上具有更高精度的压电作动器SVM迟滞模型。通过减小训练集中所包含输入信号频率的间隔,提高了模型在测试集上的精度。采用交叉验证的方法确定SVM模型中的参数,提高了迟滞模型在全局上的精度和泛化能力。结果表明,相比传统Bouc-Wen模型,所提出的模型在1 Hz处精度提高了8倍,在50 Hz处精度提高了60倍。通过位移跟踪实验,证明了基于SVM迟滞逆模型的前馈+反馈(FF+FB)控制能够有效提高跟踪精度,相较于PID反馈控制,其跟踪误差最多可降低73.9%。     

超磁致伸缩致动器的小脑神经网络前馈逆补偿-模糊PID控制

针对超磁致伸缩致动器(GMA)在精密致动控制中存在的迟滞和位移非线性,提出了小脑神经网络(CMAC)前馈逆补偿结合模糊PID控制的新策略。通过小脑神经网络(CMAC)学习获得超磁致伸缩致动器动态逆模型用于对超磁致伸缩致动器迟滞非线性进行补偿;利用模糊PID控制降低小脑神经网络(CMAC)学习时的误差和抑制扰动,提高系统的跟踪控制性能,从而实现超磁致伸缩致动器的精密致动控制。仿真和实验结果表明:所采用的控制策略有效地消除了迟滞非线性的影响,系统的跟踪误差降低到了5%以下,而位移跟踪误差均方差仅为0.58。此外,这种策略的特点是学习和控制同时进行,控制系统能够适应被控对象动态特性的变化,使系统具有较强的鲁棒性,同时也能够有效地抑制外界的干扰,提升系统的自适应控制性能。     

压电作动器的率相关迟滞建模与跟踪控制

为了降低率相关迟滞特性对压电作动器的影响,研究了基于Hammerstein模型的建模方法和实时跟踪控制策略。以改进的Prandtl-Ishlinskii(MPI)模型表示静态非线性部分,以外因输入自回归模型(Autoregressive Model with Exogenous Input ARX)表示动态线性部分,建立了能够描述压电作动器率相关迟滞特性的Hammerstein模型。基于所建Hammerstein模型,设计了基于前馈自适应逆补偿和PI反馈的复合控制策略。最后,设计并实现了基于前馈逆补偿和PI反馈的复合控制策略来对比和验证所设计的控制策略的有效性。验证实验显示:采用文中设计的控制策略实时跟踪100Hz以内,幅值为11μm的单一频率信号和扫频信号以及变幅值的复合频率信号和正弦扫描信号时,均方根误差为0.280 8~0.437 3μm,相对误差为0.016 5~0.024 4,并且具有良好的实时性能。与基于前馈逆补偿和PI反馈的复合控制策略相比,提出的基于前馈自适应逆补偿和PI反馈的复合控制策略具有更高的跟踪精度。     

宏纤维复合材料MFC作动器迟滞非线性分析与补偿方法研究

作为一种新型的压电纤维复合材料作动器,宏纤维复合材料MFC(Macro fiber composite)具有响应迅速、机电换能效率高、封装完备和环境适应性强等特点,广泛应用于工程结构的振动、主动变形控制的领域。然而压电材料所固有的迟滞非线性特性直接影响着作动器的控制精度和驱动效果。构造MFC作动器驱动的悬臂梁结构的试验系统,建立基于试验数据的PI(Prandtl-Ishlinskii)和修正PI迟滞模型,进而开展针对主动控制的迟滞逆补偿模型研究。通过试验对这两种模型的准确性和逆补偿的有效性进行比较,结果表明修正的PI迟滞模型对MFC作动器的迟滞非线性特性具有良好的补偿结果,修正的PI逆模型的拟合位移是未进行电压补偿控制的2.14倍,是PI逆模型补偿控制的1.56倍。所发展的修正PI迟滞模型研究方法可以推广到其他压电材料迟滞行为的模拟。     

压电陶瓷执行器的神经网络实时自适应逆控制

目的：为了提高压电陶瓷执行器执行精度,提出消除压电陶瓷的非线性、非光滑的迟滞特性的方法。 方法：提出了基于内积的压电陶瓷动态神经网络非线性、非光滑的迟滞逆模型,采用反馈误差学习方法,避免了求取压电陶瓷的Jacobian信息,快速地在线得到压电陶瓷的逆模型,并结合PID反馈控制,在dSPACE系统平台上,实现压电陶瓷的神经网络自适应逆控制,为了提高实时性,程序采用效率高、速度快的C-MEX S Function编程。结果：实验结果表明：神经网络自适应逆控制的控制精度为：0.13μm,而PID控制精度为：0.32μm 。结论：所提出方法有效地消除了迟滞的影响,控制精度高。     

压电陶瓷作动器非对称迟滞的建模与补偿控制

针对传统Bouc-Wen模型不能反映压电陶瓷作动器迟滞的非对称特性而导致其补偿控制精度难以提高的问题,提出了一种改进Bouc-Wen模型,通过修改形状控制参数使其能够模拟压电陶瓷作动器的非对称迟滞曲线.利用粒子群优化算法辨识了所需的模型参数,进一步研究了基于模型的前馈补偿控制、前馈加PI反馈补偿控制对于实现高精度位移输出的效果;在开环前馈补偿控制实验中,采用改进Bouc-Wen模型比传统Bouc-Wen模型的控制误差可降低约42％;在前馈加PI反馈补偿控制实验中,采用改进Bouc-Wen模型比传统Bouc-Wen模型的控制误差可降低约20％.研究结果表明:在相同的控制方式下,采用改进Bouc-Wen模型能够得到比传统Bouc-Wen模型更高的轨迹跟踪精度;与单纯采用基于模型的前馈补偿控制相比,采用基于模型的前馈加PI反馈补偿控制可显著提高压电陶瓷作动器的位移输出精度.     

菱形微位移压电作动器输入输出杂交建模

针对某定位装置,研究了一种新型菱形微位移压电作动器,该压电作动器由压电堆、菱形位移放大机构以及柔性铰链组成。菱形微位移压电作动器的核心驱动部件为压电堆,由于压电材料的迟滞特性,菱形压电作动器具有非线性迟滞特性。为了消除迟滞对压电作动器在后续控制中的影响,发展了一种Preisach杂交建模的方法,该方法在传统Preisach模型的基础上,有效结合了Preisach离散模型和支持向量机(support vector machine,简称SVM),建立了微位移压电作动器输入输出杂交模型。试验结果表明,SVM有效解决了因1阶滞回曲线数量不足而导致Preisach模型精度低的问题,同时与传统Preisach模型相比,杂交建模能更准确地描述迟滞特性,具有更高的精度。     

Ultra-precise tracking control of piezoelectric actuators via a fuzzy hysteresis model

In this paper, a novel Takagi-Sugeno (T-S) fuzzy system based model is proposed for hysteresis in piezoelectric actuators. The antecedent and consequent structures of the fuzzy hysteresis model (FHM) can be, respectively, identified on-line through uniform partition approach and recursive least squares (RLS) algorithm. With respect to controller design, the inverse of FHM is used to develop a feedforward controller to cancel out the hysteresis effect. Then a hybrid controller is designed for high-performance tracking. It combines the feedforward controller with a proportional integral differential (PID) controller favourable for stabilization and disturbance compensation. To achieve nanometer-scale tracking precision, the enhanced adaptive hybrid controller is further developed. It uses real-time input and output data to update FHM, thus changing the feedforward controller to suit the on-site hysteresis character of the piezoelectric actuator. Finally, as to 3 cases of 50 Hz sinusoidal, multiple frequency sinusoidal and 50 Hz triangular trajectories tracking, experimental results demonstrate the efficiency of the proposed controllers. Especially, being only 0.35% of the maximum desired displacement, the maximum error of 50 Hz sinusoidal tracking is greatly reduced to 5.8 nm, which clearly shows the ultra-precise nanometer-scale tracking performance of the developed adaptive hybrid controller.     

Real-time inverse hysteresis compensation of piezoelectric actuators with a modified Prandtl-Ishlinskii model

This paper presents a novel real-time inverse hysteresis compensation method for piezoelectric actuators exhibiting asymmetric hysteresis effect. The proposed method directly utilizes a modified Prandtl-Ishlinskii hysteresis model to characterize the inverse hysteresis effect of piezoelectric actuators. The hysteresis model is then cascaded in the feedforward path for hysteresis cancellation. It avoids the complex and difficult mathematical procedure for constructing an inversion of the hysteresis model. For the purpose of validation, an experimental platform is established. To identify the model parameters, an adaptive particle swarm optimization algorithm is adopted. Based on the identified model parameters, a real-time feedforward controller is implemented for fast hysteresis compensation. Finally, tests are conducted with various kinds of trajectories. The experimental results show that the tracking errors caused by the hysteresis effect are reduced by about 90%, which clearly demonstrates the effectiveness of the proposed inverse compensation method with the modified Prandtl-Ishlinskii model.     

Hybrid controller of a linear piezoelectric walking stage relying on stack/shear piezoelectric actuators

This paper proposes a hybrid control strategy of a novel linear piezoelectric walking stage based on two sorts of piezoelectric actuators, which takes the load variation into account. The proposed stage consists of two parallel 4-bar lever amplification mechanisms with flexure hinges actuated by piezoelectric stacks to heighten the vertical distance (that is more tolerable to the assembly discrepancy), two compression springs (that is able to maintain a fixed linear position without powering), and two shear piezoelectric actuators (that can achieve longer and equivalent to walking motion) in a small form factor. The proposed stage has two operating modes, namely a coarse positioning mode with a more extensive travel range and a fine positioning mode with a nanometer-level resolution, to possess excellent performance for the linear piezoelectric walking stage of load variations. One multimodal switching controller and one feedforward-feedback controller conduct the coarse mode and fine mode, respectively. The optimal frequency for a specific load is obtained through a backpropagation neural network in the multimodal switching control. In the feedforward-feedback control, the inverse mathematical model based on the Bouc-Wen hysteresis model is used to mitigate the hysteresis effect in the feedforward part while the proportional–integral–derivative controller in the feedback part handles the external system disturbances. Experimental results show the proposed hybrid coarse/fine mode control strategy's effectiveness to satisfy an efficient and accurate positioning task.     

Controller design for high-frequency cutting using a piezo-driven microstage

Controller design consists of a feedforward and a feedback controller to support a microstage with flexure hinge structure driven by piezoelectric ceramic actuator for high-frequency nanoscale cutting is developed in this article. The feedforward controller is designed based on a hysteresis dynamic model in order to reduce the nonlinear hysteresis effect of piezoelectric actuator. The position feedback controller is designed based upon an exponentially weighted moving average (EWMA) method embedded in an internal model control (IMC) structure constructing a run-to-run IMC (RtR-IMC) control scheme in order to deal with system bias or modeling inaccuracy. Also, disturbance due to temperature rise will influence actuator's performance, hence an additional compensator is included in the IMC structure. Surfaces dimple micro-machining utilizes piezoelectric-driven microstage for high-speed cutting is selected as an example to investigate system performance. The developed control algorithm is implemented on a DSP-based system to provide 1 kHz operating speed. In experiment, the proposed feedforward and feedback controller is verified to be able to overcome those negative factors efficiently and preserve good positioning accuracy.     

PBP驱动器率相关迟滞特性研究及其线性化控制

后屈曲预压缩压电双晶片(Post-buckling pre-compression,PBP)驱动器作为一种大行程压电舵机驱动器,存在着严重的率相关迟滞现象。为了使PBP驱动器能够作为具有较高控制精度的微小型飞行器舵机驱动器,利用基于Bouc-Wen模型的Hammerstein率相关迟滞模型对其进行参数识别,并通过试验验证了该模型能够较好地预测PBP驱动器的率相关迟滞特性;在此基础上为PBP驱动器设计一种具有在线自适应能力的前馈单神经元PID复合线性化控制器,在多种单复合频率信号作用下对其控制回路进行位移跟踪半实物仿真试验,并与基于径向基函数(Radial basis function,RBF)神经网络PID控制器进行对比,结果表明前馈单神经元PID控制器具有更快的响应速度和更高的控制精度。     

Measurement and calibration for Stewart micromanipulation system

In this article, hysteresis controller design and static error compensation method for a 6-dof micro-positioning platform driven by piezoelectric actuator is studied. The nonlinear hysteresis effect of the piezoelectric actuator is analyzed by means of Preisach model. Its inverse model is used as the feedforward controller. Error compensation method is designed to compensate manufacture error and assembly error by use of the developed 3-points-3-axes measurement method. From practical experiment, the proposed method makes improvement on the accuracy of positioning.     

基于模糊干扰观测器的电动Stewart平台自适应模糊控制

建立了一个电动Stewart平台的统一动力学模型,并基于它设计了一种新型的自适应模糊控制算法。这个统一的动力学模型在任务空间中使用了Newton-Euler方法建立,同时结合了平台动力学和执行器动力学模型。自适应模糊控制算法使用计算力矩方法设计运动平台标称模型的逆动力学控制器,然后使用基于模糊干扰观测器的自适应模糊控制器对模型的不确定性和外部扰动进行补偿。通过数值仿真分析表明,在不引入高增益控制器的情况下,成功地消除了平台参数的不确定性和外部干扰的影响,保证了平台的跟踪性能。     

Design,modeling, and control of a monolithic compliant x-y-θ microstage using a double-rocker mechanism

This paper reports the design, modeling, and control of a novel three-degrees-of-freedom piezoelectric compliant microstage by introducing a new double-rocker mechanism. The double-rocker mechanism combines a first (leverage) amplifier and a second (rocker) amplifier for double-stage displacement amplification and parasitic motion reduction. An analytical model is established to calculate the deformation behavior of the microstage, and the model is verified using finite-element analysis (FEA). An improved Prandtl-Ishlinskii (PI) model is proposed to describe piezoelectric hysteresis characteristics by optimizing the threshold selection. Then, a composite control strategy is designed to achieve precision trajectory control. The control strategy consists of a hysteresis-based feedforward controller and a proportional-integral feedback controller. A prototype of the microstage is manufactured, and an experimental system is established. Several open-loop and closed-loop experiments are conducted, and the experimental results validate the effectiveness of the proposed microstage and the designed control strategy.