辨识参数带约束的最小二乘法估计

通过讨论系统输入输出的极限形式,给出了系统参数的一个约束条件。在此约束条件下讨论系统的参数估计问题,给出了系统参数约事条件的最小二乘估计,由于在约束条件中随机干扰的影响几乎可以忽略,因此可以较准确地反映辨识参数间线性关系,仿真例子表明,这种带约束的最小二乘估计比最小二乘估计具有更高的辨识精度。     

基于矩阵分式多项式时变结构模态参数最小二乘辨识

基于时间相关矩阵分式多项式传递函数模型,给出线性时变结构时频域参数化模型。以时频域参数化模型为基础,将现有广泛用于时不变结构模态参数辨识的最小二乘复指数法拓展到时频域,提出基于矩阵分式多项式模型的时频域线性时变结构模态参数最小二乘辨识方法;针对时频域最小二乘对计算资源庞大需求问题,给出基于缩减正则方程的最小二乘问题求解方法。通过对两质量连续变化三自由度时变结构仿真算例,说明最小二乘中待估参数约束对模态参数辨识影响,阐述所提线性时变结构模态参数辨识方法特点,说明方法的有效性及潜在实用性。     

结构应变模态参数辨识的最小二乘复频域方法

由于应变模态对结构状态的敏感性,其在结构在线健康监测和损伤识别方面比位移模态更具优势。利用应变和位移的关系,将最小二乘复频域方法应用到结构应力应变分析中,建立基于应变测量数据的结构动力学参数频域辨识方法。由于应变模态和位移模态是同一种物理状态的不同表达形式,两者在数学表达上有相似性。首先建立以应变为变量的参数化公分母模型,在此基础上将非线性最小二乘问题进行线性化,得到加权线性最小二乘的方程误差。然后采用基于缩减正则方程的算法进行求解,减少计算量,并通过对模型参数施加约束来避免参数冗余。然后,设计并搭建一个自由梁的实验结构系统,利用光纤布拉格光栅应变传感器测量结构动应变数据,根据最小二乘复频域方法,基于应变测量数据辨识得到频率和阻尼比,与传统的基于加速度测量数据的辨识结果相吻合。另外,辨识所得应变模态振型与仿真结果也具有一致性。因此,数值仿真和实验验证表明,文中提出的基于最小二乘复频域方法能够准确辨识结构应变模态。     

基于最小二乘支持向量机的传感器非线性动态系统辨识

讨论了一种基于最小二乘支持向量机的非线性动态传感器系统辨识方法,并给出了相应的推导过程和学习算法.首先,将传感器的非线性动态系统分解为静态非线性子环节和动态线性子环节串联--Hammerstein模型;然后,建立类似线性的中间模型,通过该模型能将Hammerstein模型的非线性传递函数转换为等价的类线性形式;再通过LS-SVM线性回归算法求取中间模型参数;最后推导出中间模型参数与Hammerstein模型参数之间的关系,并通过该关系反演出原传感器系统的Hammerstein模型参数,实现传感器非线性动态辨识.仿真与实际传感器系统辨识的实验结果均表明该方法可行.     

双最小二乘法在结构振动模态参数时域识别中的应用

本文编制了模态参数时域识别的双最小二乘法程序,并进行了模拟试验。试验结果表明:使用双最小二乘法识别阻尼系数优于使用单最小二乘法,同时振型和固有频率的识别精度不会降低。利用某动平衡试验装置前端转子系统的横向振动的自由响应数据,对横向振动的固有频率、振型和阻尼系数进行了识别。得出的固有频率值与振动自由响应的谱分析得到的固有频率值极为接近。     

基于前向神经网络的时变非线性结构系统辨识快速递推最小二乘法

针对基于前向神经网络的普通递推最小二乘估计存在着自适应跟踪慢和精度低的问题，提出了一种可对非线性时变系统进行快速辨识的新方法，因该方法有类似递推最小二乘算法的形式，称其为基于前向神经网络的快速递推最小二乘算法。该算法对传统的递推最小二乘算法的递推方式进行了改变，以更好的跟踪非线性时变系统的动态特性。针对典型的系统辨识仿真算例，通过与现有常用方法的比较研究显示了这种算法具有计算简单、收敛速度快和辨识精度高的良好性能。最后将方法用于一个三自由度时变非线性振动系统，结果同样验证了方法的良好特性。     

非线性最小二乘问题的一个自适应算法

本文简要介绍了非线性最小二乘问题的一个自适应算法的基本理论和计算步骤测试例子说明该算法的收敛速度快,对初值要求宽松,大大优于Gauss-Newton类算法。     

基于改进最小二乘步骤的NARMA模型辨识非线性时变结构系统

基于时变非线性自回归滑动平均模型利用改进的递推最小二乘算法提出一种用于非线性时变结构系统辨识的方法。利用线性变换将非线性时不变结构系统的动力学模型转化为非线性自回归滑动平均模型,然后将非线性项展开为系统输出数据的多项式的形式。利用短时时不变假设,通过改变模型的参数跟踪系统参数的变化,将非线性时变系统的辨识问题转化为线性时变系统的辨识问题,再利用改进的递推最小二乘算法实现对非线性时变结构系统的辨识。最后通过一个具有非线性时变刚度的三自由度结构系统的仿真算例表明,该方法可以有效地辨识非线性时变结构系统。     

相位噪声函数的非线性最小二乘曲线拟合

相位噪声是对频率源频率稳定性的表示,对其幂律谱函数进行拟合,在仿真中非常重要,首先介绍线性最小二乘曲线拟合及非线性最小二乘曲线拟合的原理,然后结合非线性最小二乘曲线拟合函数,对相位噪声幂律谱进行拟合仿真。     

精确的炮弹定位方法——非线性最小二乘法

利用非线性最小二乘法建立模型，用MATLAB求解并进行灵敏度分析。得到炮弹精确的坐标位置。利用该方法能够精确解算出弹道。     

基于非线性振动的斜拉索参数识别无模型方法

基于非线性振动理论提出了斜拉索参数识别的无模型方法.该方法以由奇异摄动法所获得的斜拉索自振频率解析表达式为依据,根据斜拉索频率测试结果和计算值之差构建目标函数,将斜拉索索力、索长等关键参数作为待识别参数,采用最优化方法实现参数识别.通过试验验证了方法的有效性并和有模型方法的识别结果进行了对比.研究表明,所提出的方法可以显著提高斜拉索动力响应分析结果的准确性;无模型方法和有模型方法精度相当.而无模型方法在求解效率、方法的易用性等方面更具优越性,更便于实际工程应用.     

On-line identification, flutter testing and adaptive notching of structural mode parameters for V-22 tiltrotor aircraft

New algorithms and results are presented for flutter testing and adaptive notching of structural modes in V-22 tiltrotor aircraft based on simulated and flight-test data from Bell Helicopter Textron, Inc. (BHTI). For flutter testing and the identification of structural mode frequencies, dampings and mode shapes, time domain state space techniques based on Deterministic Stochastic Realization Algorithms (DSRA) are used to accurately identify multiple modes simultaneously from sine sweep and other multifrequency data, resulting in great savings over the conventional Prony method. Two different techniques for adaptive notching are explored in order to design an Integrated Flight Structural Control (IFSC) system. The first technique is based on on-line identification of structural mode parameters using DSRA algorithm and tuning of a notch filter. The second technique is based on decoupling rigid-body and structural modes of the aircraft by means of a Kalman filter and using rigid-body estimates in the feedback control loop. The difference between the two approaches is that on-line identification and adaptive notching in the first approach are entirely based on the knowledge of structural modes, whereas the Kalman filter design in the second approach is based on the rigid-body dynamic model only. In the first IFSC design, on-line identification is necessary for flight envelope expansion and to adjust the notch filter frequencies and suppress aero-servoelastic instabilities due to changing flight conditions such as gross weight, sling loads, and air speed. It is shown that by tuning the notch filter frequency to the identified frequency, the phase lag is reduced and the corresponding structural mode is effectively suppressed and stability is maintained. In the second IFSC design using Kalman filter design, the structural modes are again effectively suppressed. Furthermore, the rigid-body estimates are found to be fairly insensitive to both natural frequency and damping factor variations and therefore stability is maintained. The Kalman filter design might be a better choice when the rigid-body dynamics are well known because no adaptation is necessary in this case.     

改进的受力状态映射法在结合部动力学参数辨识中应用

针对受力状态映射法作为辨识非线性结合部参数重要方法具有物理意义明确、辨识准确等特点,而实际辨识试验时结构某些参数难以测定、致辨识过程困难等问题,提出结合子结构模态综合法的受力状态映射法,可有效解决该问题。参数辨识过程中对模型易出现的缺失项及冗余项,利用基于TSVD(Truncated Singular Value Decomposition)正则化方法的模型迭代修正法。仿真模型表明,修正模型较精确模型误差小、辨识精度高。通过对导轨结合部进行参数辨识实验研究,证明辨识方法的有效性及准确性。     

An inverse finite‐element algorithm for parameter identification of thermoelastic damage models

In this contribution an algorithm for parameter identification of thermoelastic damage models is proposed, in which non‐uniform distributions of the state variables such as stresses, strains, damage variables and temperature are taken into account. To this end a least‐squares functional consisting of experimental data and simulated data is minimized, whereby the latter are obtained with the finite‐element method. In order to improve the efficiency of the minimization process, a gradient‐based optimization algorithm is applied, and therefore the corresponding sensitivity analysis for the coupled variational problem is described in a systematic manner. For illustrative purpose, the performance of the algorithm is demonstrated for a non‐homogeneous shear problem with thermal loading. Copyright © 2000 John Wiley & Sons, Ltd.     

一种新的非线性系统脊骨线提取方法

脊骨线对于非线性系统的判断、描述和参数识别,具有重要的意义;而现有的脊骨线提取方法大多理论上较为复杂,且有局部线性化误差较大、数据波动剧烈等问题,限制了工程应用。提出一种新的非线性系统脊骨线提取方法,该方法利用非线性系统自由振动响应的一次谐波分量,计算谐波信号峰值点的瞬时频率,可以方便地提取脊骨线;这种新的非线性系统脊骨线提取方法理论明确、简单,计算方便,易于工程应用。通过三个数值算例说明了该方法的有效性,同时将此方法应用于非线性描述,并综合讨论了非线性描述的几何方法;并基于此方法进行了非线性系统参数识别,取得了良好的效果。     

Comparison of Bayesian methods on parameter identification for a viscoplastic model with damage

The state of materials and accordingly the properties of structures are changing over the period of use, which may influence the reliability and quality of the structure during its life-time. Therefore, identification of the model parameters of the system is a topic which has attracted attention in the content of structural health monitoring. The parameters of a constitutive model are usually identified by minimization of the difference between model response and experimental data. However, the measurement errors and differences in the specimens lead to deviations in the determined parameters. In this article, the focus is on the identification of material parameters of a viscoplastic damaging material using a stochastic simulation technique to generate artificial data which exhibit the same stochastic behavior as experimental data. It is proposed to use Bayesian inverse methods for parameter identification and therefore the model and damage parameters are identified by applying the Transitional Markov Chain Monte Carlo Method (TMCMC) and Gauss–Markov–Kalman filter (GMKF) approach. Identified parameters by using these two Bayesian approaches are compared with the true parameters in the simulation and with each other, and the efficiency of the identification methods is discussed. The aim of this study is to observe which one of the mentioned methods is more suitable and efficient to identify the model and damage parameters of a material model, as a highly non-linear model, using a limited surface displacement measurement vector and see how much information is indeed needed to estimate the parameters accurately.     

大容量蓄电池组的数学建模及参数辨识

建立了铅酸蓄电池组的数学模型，采用对大容量铅酸蓄电池组进行突加扰动的试验方法，对不同容量的蓄电池组开展了实验研究，验证了所建模型并辨识出蓄电池组的参数。通过对不同状态的蓄电池组的参数辨识，发现其参数几乎不变。     

二元机翼非线性颤振系统的若干分析方法

颤振是气动弹性力学研究最重要的问题之一。本文综述了亚音速条件下二元机翼非线性颤振研究的若干分析方法。目前,基于二元机翼的非线性颤振分析采用的定性方法主要是常微分方程定性理论,定量方法则有等效线性化法、描述函数法、谐波平衡法以及摄动法等。对所提及的方法做了简要的评述和比较,指出了进一步研究的问题。     

Issues in optimal parameter estimation for the nonlinear Muskingum flood routing model

This study answers two questions raised in the parameter estimation optimization for the nonlinear Muskingum flood routing model. The first question is whether a new global optimum was still found after the existing global optimum had already been found. In order to fairly verify this question, a standard routing procedure for the nonlinear Muskingum model, which has not been clearly described previously, is proposed. Because the routing procedure was coded in a spreadsheet, any researcher can easily test it after downloading it. The second question is the reason why various approaches, such as Lagrange multiplier, Broyden–Fletcher–Goldfarb–Shanno (BFGS), genetic algorithm, harmony search and particle swarm optimization, have tackled only Wilson's data set as the parameter estimation optimization for the nonlinear Muskingum model, because Wilson's data have a unique structure which is differentiated from other data sets. This study also provides various data sets to compare.