基于加速度信号的柔性板的挠性参数辨识简

以柔性板为对象,开展了结构挠性参数辨识技术的研究. 给出了一种基于加速度信号输出的特征系统实现算法的计算格式,基于粒子群优化算法给出了加速度传感器在柔性板上的优化位置. 仿真结果显示,粒子群方法能够有效地确定出传感器在板上的优化位置,特征系统实现算法能够有效地辨识出结构的挠性参数.     

基于粒子群算法的时滞动力学系统时滞辨识

以柔性悬臂梁为对象,对主动控制中的时滞辨识问题进行了研究。研究中将时滞辨识问题转化为一个优化问题,以系统某一段时间段的真实响应与预估响应之差的绝对值之和作为目标函数,采用粒子群算法作为优化算法。仿真中分别考虑了单时滞和双时滞辨识两种情况,结果表明,该时滞问题辨识方法能够有效地辨识出系统中的时滞量。     

基于微粒群算法优化支持向量机的加速度计静态模型辨识

针对加速度计静态模型采用线性近似模型辨识存在较大误差的问题,利用支持向量回归在小样本、非线性及高维特征空间中具有很好的推广能力的优点,提出了一种利用支持向量回归进行加速度计静态模型辨识的方法.为了避免随机试凑法识别支持向量回归参数费时的问题,采用高效的并行搜索算法-微粒群算法进行支持向量回归参数优化.利用精密光学分度头对石英挠性加速度计进行了12位置静态翻滚试验,试验结果表明所提方法可以精确地对石英挠性加速度计静态模型进行辨识,其模型精度比最小二乘辨识法的模型精度提高一倍以上.     

密集模态挠性结构模型多变量频域辨识和控制

密集模态挠性结构的模态不仅阻尼小而且耦合程度高,给模型辨识带来了很大困难.频域辨识是获取空间挠性结构模型的一个有效方法,但是目前频域辨识要么模型结构定义有缺陷,要么是集中在单变量情形,不适合作大型空间挠性结构多变量模型的辨识.本文提出了多变量极大似然频域辨识,给出了其模型结构定义、算法推导及实现,并将其应用于H型密集模态挠性板的模型辨识,根据辨识结果,设计主动控制律,实现了对密集模态挠性板振动的有效抑制,表明了辨识算法及主动控制的可行性.     

石英挠性加速度计温度补偿算法

石英挠性加速度是惯性导航系统核心的惯性器件之一,其输出精度受到温度变化的影响,为了降低温度对石英挠性加速度计精度的影响,在研究石英挠性加速度计数学模型的系数随温度变化规律的基础上,设计了加速度计温度模型辨识试验方法,利用数据拟合方法建立了加速度计温度模型。应用该模型提出了石英挠性加速度温度补偿算法,针对该算法的有效性,进行了实验验证,结果表明应用该温度补偿算法,可使加速度计的测量精度提高一个数量级,补偿效果明显。该温度补偿算法可有效地应用于捷联式惯性导航系统等领域中。     

基于粒子群优化的UKF在SINS/GPS组合导航中的应用

针对组合导航中使用传统Kalman滤波方法时噪声协方差矩阵参数需要耗时耗力反复试验得到的问题,提出利用粒子群优化算法对卡尔曼滤波器的滤波参数Q和R进行寻优后用于组合导航的方法。将滤波参数Q和R作为粒子进行寻优,将粒子群算法优化得到的滤波参数值作为卡尔曼滤波器输入参数,用于SINS/GPS组合导航系统。仿真实验结果表明,12次实验中粒子群算法搜索出的参数均值分别为0.0208(°)/h、94.7827?g,接近所设置的噪声参数值与标准参数值0.02(°)/h、100?g。半物理实验结果表明,在实际系统中,与经验参数值用于卡尔曼滤波器相比,粒子群算法优化得到的滤波参数值位置估计精度提高了15%~30%,从而提高了组合导航性能。     

一种磨损预测的优化算法研究

根据机械部件磨损机理复杂、磨损量预测难精确的特点,提出基于免疫粒子群参数优化的最小二乘支持向量机方法预测磨损量.该算法采用免疫粒子群优化最小二乘支持向量机建模参数,避免了算法陷入局部最优解,实现了精确度高、泛化能力强的磨损量预测模型.对轴承钢试件磨损进行了试验研究,试验数据分析结果表明,基于免疫粒子群的最小二乘支持向量机预测方法优于前向反馈神经网络算法、遗传算法及蚁群算法,预测误差较小,具有很好的预测能力.     

改进PSO算法在结构作动器位置优化中的应用

针对空间结构振动主动控制中的作动器位置优化问题, 提出了一种改进的粒子群(PSO) 优化方法, 以系统总能量为性能指标进行优化; 应用改进PSO方法对算例结构进行了计算, 并与其他算法的优化结果进行了对比; 结果表明: 几种优化方法计算结果相符; 且 PSO优化算法能更有效快速地解决复杂优化问题, 从而有效地进行结构的振动控制.     

基于改进粒子群优化粒子滤波的结构损伤识别

针对粒子滤波应用于结构损伤识别问题时出现的粒子退化、反演计算强不适定性等现象,提出了一种改进的粒子群优化粒子滤波损伤识别方法。在粒子滤波算法中,利用粒子群优化过程驱使粒子群朝着后验概率密度取值较大的区域移动,优化了粒子滤波的采样过程;同时,根据结构损伤参数分布的稀疏性特点,引入对粒子群中损伤参数部分的零变异操作,既增加了粒子的多样性,又有效改善了反问题求解不适定性,提高了算法损伤识别的鲁棒性。数值仿真和框架结构振动实验结果均表明,对于线性或非线性结构,本文方法均能有效抑制噪声干扰,准确识别不同损伤工况下结构损伤的位置与程度;在试验研究中,结构损伤参数识别结果的相对误差小于1.5%。     

粒子群优化算法在传递对准中的应用

给出了一种基于粒子群优化算法的捷联惯导传递对准算法。简单分析了传递对准任务要求和主子惯导惯性器件输出之间的关系,将传递对准问题作为参数优化问题进行求解,给出了基于粒子群优化算法进行传递对准的数学模型。定义了传递对准的优化目标函数,介绍了粒子群优化算法及其应用于传递对准的具体算法设置。用粒子群优化算法求解目标函数的最小值,可获得主子惯导之间的失准角,进行一次校正即可完成传递对准过程。通过计算机仿真对算法进行了验证分析,在仿真条件下（陀螺精度为0.1°/h）,能达到方位0.1°的精度。与其他对准算法一样,算法受载体机动条件的影响较大,一般需要姿态机动来提高陀螺的信噪比。     

基于复合面/背板的平板装药防护性能

采用实验和数值模拟方法研究了橡胶复合板作为爆炸反应装甲面、背板时的防护性能,分析了两种反应装甲结构的防护机理,并与面密度相同的钢反应装甲进行了对比。实验结果表明:爆炸反应装甲面板或背板为橡胶复合板时的防护性能优于钢反应装甲,其中橡胶复合板作为背板时效果最优。数值模拟结果表明:橡胶复合板在爆炸驱动下外层钢板速度相比于钢反应装甲飞板提高16%,橡胶复合板的界面效应及其飞板间隙可以有效减小逃逸射流的长度。     

Chaos detection and parameter identification in fractional-order chaotic systems with delay

The paper first applies the 0–1 test for chaos to detecting chaos exhibited by fractional-order delayed systems. The results of the test reveal that there exists chaos in some fractional-order delayed systems with specific parameter values, which coincides with previous reports based on the phase portrait. In addition, it is very important to identify exactly the unknown specific parameters of fractional-order chaotic delayed systems in chaos control and synchronization. Thus, a method for parameter identification of fractional-order chaotic delayed systems based on particle swarm optimization (PSO) is presented. By treating the orders as parameters, the parameters and orders are identified through minimizing an objective function. PSO can efficiently find the optimal feasible solution of the objective function. Finally, numerical simulations on fractional-order chaotic logistic delayed system and fractional-order chaotic Chen delayed system show that the proposed method has effective performance of parameter identification.     

????????????????????????о?

利用X光照片对射流垂直侵彻反应装甲这一物理过程进行研究，认为爆 轰场加快了射流失稳断裂过程. 并基于射流在空气中运动断裂模型的基础上，运用弹塑性相 关理论，建立了在爆炸场中射流断裂时间模型，利用该模型得到了干扰后射的侵彻模型.     

Reduced-order models for control of fluids using the eigensystem realization algorithm

As sensors and flow control actuators become smaller, cheaper, and more pervasive, the use of feedback control to manipulate the details of fluid flows becomes increasingly attractive. One of the challenges is to develop mathematical models that describe the fluid physics relevant to the task at hand, while neglecting irrelevant details of the flow in order to remain computationally tractable. A number of techniques are presently used to develop such reduced-order models, such as proper orthogonal decomposition (POD), and approximate snapshot-based balanced truncation, also known as balanced POD. Each method has its strengths and weaknesses: for instance, POD models can behave unpredictably and perform poorly, but they can be computed directly from experimental data; approximate balanced truncation often produces vastly superior models to POD, but requires data from adjoint simulations, and thus cannot be applied to experimental data. In this article, we show that using the Eigensystem Realization Algorithm (ERA) (Juang and Pappa, J Guid Control Dyn 8(5):620?C627, 1985) one can theoretically obtain exactly the same reduced-order models as by balanced POD. Moreover, the models can be obtained directly from experimental data, without the use of adjoint information. The algorithm can also substantially improve computational efficiency when forming reduced-order models from simulation data. If adjoint information is available, then balanced POD has some advantages over ERA: for instance, it produces modes that are useful for multiple purposes, and the method has been generalized to unstable systems. We also present a modified ERA procedure that produces modes without adjoint information, but for this procedure, the resulting models are not balanced, and do not perform as well in examples. We present a detailed comparison of the methods, and illustrate them on an example of the flow past an inclined flat plate at a low Reynolds number.     

A new design method for adaptive IIR system identification using hybrid particle swarm optimization and gravitational search algorithm

Design of adaptive infinite impulse response (IIR) filter is the process of utilizing adaptive algorithm to iteratively determine the filter parameters to obtain an optimal model for the unknown plant based on minimizing the error cost function. However, the error cost surface of IIR filter is generally nonlinear, non-differentiable and multimodal. Hence, an efficient global optimization technique is required to minimize the error cost objective. A novel hybrid particle swarm optimization and gravitational search algorithm (HPSO–GSA) is proposed in this paper for IIR filter design. The proposed HPSO–GSA updates particle positions through obeying the influence of gravity acceleration in GSA and receiving direction of cognitive memory and social sharing information from PSO by means of coevolutionary strategy. The effect of key parameters on the performance of the proposed algorithm is firstly studied, and the proper parameters in HPSO–GSA are established using five benchmark plants along with the same-order model. The simulation studies have been performed for the performance comparison of eight algorithms such as PSO, GSA, QPSO, DPSO, FO-DPSO, GAPSO, PSOGSA and the proposed HPSO–GSA for unknown IIR system identification with the same-order and reduced-order filters. Simulation results show that the proposed algorithm has advantages over PSO, GSA and other PSO-based variants in terms of the convergence speed and the MSE levels.     

DYNAMIC MODELING AND ACTIVE CONTROL OF FLEXIBLE PLATE BASED ON THE INPUT-OUTPUT DATA

This paper studies the low-order dynamic modeling and active control of a flexible plate and provides experimental verification. First based on the input-output data of the system, the Markov parameters of the system are identified using the method of observer/Kalman filter identification (OKID). Then a low-order state-space model is built using the eigensystem realization algorithm (ERA). Finally, a linear quadratic Gaussian (LQG) controller is designed based on the low-order state-space model. Experimental results have proved the effectiveness and feasibility of the research.     

Approximation d'un contrôle optimal distribué par un circuit électronique réparti: application au contrôle de vibrations

This paper focuses on the design of distributed control related to distributed mechanical systems. Sensors and actuators are assumed to be numerous and periodically distributed. The problem adressed in this paper is: “Can we find a way to approximate an optimal control law with a distributed electronic circuit?” A solution to this problem is proposed in the framework of vibration control of a thin plate using piezoelectric actuators and sensors.     

An optimization of a multi-layered plate under ballistic impact

This paper may be the first trial regarding the optimal design of a multi-layered plate under ballistic impact. An optimal design of a multi-layered plate to endure ballistic impact is suggested by using size optimization based on numerical simulations. The NET2D, a Lagrangian explicit time-integration finite element code for impact analyses, is used to find the optimal parameter values. Three different materials such as mild steel and aluminum for a multi-layered plate structure and die steel for the pellet are assumed. In order to consider the effects of strain rate hardening, strain hardening and thermal softening, the Johnson–Cook model is used as the constitutive models for the simulation. Several mesh types of different size and aspect ratio are tried to check the effect of mesh on the solution and to obtain the appropriate mesh density. The measuring domain is selected to reduce the analyzing time without affecting the sensitivity.The response surface method based on the design of experiments is used to obtain the optimal design. The average temperature or the equivalent plastic strain is introduced as a response for the optimization of the impact problem. Furthermore, the perforation criteria with the equivalent plastic strain to determine whether the plate structure is perforated or not is suggested. The optimized thickness of each layer in which perforation does not occur and the strength of multi-layer is maximized is obtained at a constant velocity of a pellet with a designated total thickness.