STOCHASTIC DYNAMIC SENSITIVITY OF UNCERTAIN STRUCTURES SUBJECTED TO RANDOM EARTHQUAKE LOADING

The present study involves computation of stochastic sensitivity of structures with uncertain structural parameters subjected to random earthquake loading. The formulations are provided in frequency domain. A strong earthquake-induced ground motion is considered as a random process defined by respective power spectral density function. The uncertain structural parameters are modelled as homogeneous Gaussian stochastic field and discretized by the local averaging method. The discretized stochastic field is simulated by the Cholesky decomposition of respective co-variance matrix. By expanding the dynamic stiffness matrix about its reference value, the advantage of Neumann Expansion technique is explored within the framework of Monte Carlo simulation, to compute responses as well as sensitivity of response quantities. This approach involves only a single decomposition of the dynamic stiffness matrix for the entire simulated structure and the facility that several stochastic fields can be tackled simultaneously are basic advantages of the Neumann Expansion. The proposed algorithm is explained by an example problem.     

Uncertainty propagation in SEA for structural–acoustic coupled systems with non-deterministic parameters

Considering limited available information on uncertainties in structural - acoustic coupled systems, two methods namely the vertex method and the Legendre orthogonal polynomial based method for predicting their dynamic behavior are developed based on the Statistical Energy Analysis (SEA) approach. For the vertex method, an efficient program for determining coordinates of all vertices of the rectangular spanned by entries of the involved interval input vector is coded, which is well suited for an interval input vector in arbitrary dimension. Instead of calculating the extremum of the response of interest, a method for determining its minimal and maximal point vectors dimension by dimension with respect to uncertain parameters is proposed based on the Legendre orthogonal polynomial approximation. Following the theoretical analysis of the accuracy and efficiency of the proposed methods, their validation is performed by one numerical example and two applications.     

Modified perturbation method for eigenvalues of structure with interval parameters

In overcoming the drawbacks of traditional interval perturbation method due to the unpredictable effect of ignoring higher order terms,a modified parameter perturbation method is presented to predict the eigenvalue intervals of the uncertain structures with interval parameters.In the proposed method,interval variables are used to quantitatively describe all the uncertain parameters.Different order perturbations in both eigenvalues and eigenvectors are fully considered.By retaining higher order terms,the original dynamic eigenvalue equations are transformed into interval linear equations based on the orthogonality and regularization conditions of eigenvectors.The eigenvalue ranges and corresponding eigenvectors can be approximately predicted by the parameter combinatorial approach.Compared with the Monte Carlo method,two numerical examples are given to demonstrate the accuracy and efficiency of the proposed algorithm to solve both the real eigenvalue problem and complex eigenvalue problem.     

Observer-based passive control for uncertain linear systems with delay in state and control input

This paper deals with the robust passivity synthesis problem for a class of uncertain linear systems with time-varying delay in state and control input. The parameter uncertainties are norm-bounded and allowed to appear in all matrices of the model. The problem aims at designing an observer-based dynamic output-feedback controller that robustly stabilizes the uncertain systems and achieves the strict passivity of closed-loop systems for all admissible uncertainties. By converting the problem at hand into a class of strictly passive control problem for a parameterized system, the explicit solution is established and expressed in terms of a linear matrix inequality. A numerical example is provided to demonstrate the validity of the proposed approach.     

不确定混沌系统的径向基函数神经网络反馈补偿控制

对不确定混沌系统控制问题, 研究了一种基于径向基函数神经网络(radial basis function neural network, RBFNN)的反馈补偿控制方法. 该方法首先用RBFNN对混沌系统的动力学特性进行学习, 然后用训练好的RBFNN模型对混沌系统进行反馈补偿控制. 该方法的特点是不需要被控混沌系统的数学模型,可以快速跟踪任意给定的参考信号. 数值仿真试验表明了该控制方法不仅具有响应速度快、控制精度高, 而且具有较强的抑制混沌系统参数摄动能力和抗干扰能力.     

Modelling the spindle–holder taper joint in machine tools: A tapered zero-thickness finite element method

This study presents a tapered zero-thickness finite element model together with its parameter identification method for modelling the spindle–holder taper joint in machine tools. In the presented model, the spindle and the holder are modelled as solid elements and the taper joint is modelled as a tapered zero-thickness finite element with stiffness and damping but without mass or thickness. The proposed model considers not only the coupling of adjacent degrees of freedom but also the radial, tangential and axial effects of the spindle–holder taper joint. Based on the inverse relationship between the dynamic matrix and frequency response function matrix of a multi-degree-of-freedom system, this study proposes a combined analytical–experimental method to identify the stiffness matrix and damping coefficient of the proposed tapered zero-thickness finite element. The method extracts those parameters from FRFs of an entire specimen that contains only the spindle–holder taper joint. The simulated FRF obtained from the proposed model matches the experimental FRF quite well, which indicates that the presented method provides high accuracy and is easy to implement in modelling the spindle–holder taper joint.     

The time response of structures with bounded parameters and interval initial conditions

Uncertainty plays an important role in the performance of structures. In this paper, we focus on the dynamic response of structures with bounded parameters and interval initial conditions, and present a new method to determine the supremum and infimum of the time response. The method is based on the vertex solution theorem for the first-order deviation of the dynamic response from its central value and avoids interval extension problems present in current methods, where the length of the interval increases significantly due to the intermediate calculations. The method is more accurate than existing perturbation methods and provides tighter bounds on the response. The approach neglects the second-order terms in the equation of motion, and care should be exercised when the parameter variations are large. The other advantage of this method is its ability to solve problems with uncertainties in the initial conditions.     

Robust H∞ control of active vehicle suspension under non-stationary running

Due to complexity of the controlled objects, the selection of control strategies and algorithms in vehicle control system designs is an important task. Moreover, the control problem of automobile active suspensions has been become one of the important relevant investigations due to the constrained peculiarity and parameter uncertainty of mathematical models. In this study, after establishing the non-stationary road surface excitation model, a study on the active suspension control for non-stationary running condition was conducted using robust H_∞ control and linear matrix inequality optimization. The dynamic equation of a two-degree-of-freedom quarter car model with parameter uncertainty was derived. The H_∞ state feedback control strategy with time-domain hard constraints was proposed, and then was used to design the active suspension control system of the quarter car model. Time-domain analysis and parameter robustness analysis were carried out to evaluate the proposed controller stability. Simulation results show that the proposed control strategy has high systemic stability on the condition of non-stationary running and parameter uncertainty (including suspension mass, suspension stiffness and tire stiffness). The proposed control strategy can achieve a promising improvement on ride comfort and satisfy the requirements of dynamic suspension deflection, dynamic tire loads and required control forces within given constraints, as well as non-stationary running condition.     

Optimal UAV Formation Tracking Control with Dynamic Leading Velocity and Network-Induced Delays

With the rapid development of UAV technology, the research of optimal UAV formation tracking has been extensively studied. However, the high maneuverability and dynamic network topology of UAVs make formation tracking control much more difficult. In this paper, considering the highly dynamic features of uncertain time-varying leader velocity and network-induced delays, the optimal formation control algorithms for both near-equilibrium and general dynamic control cases are developed. First, the discrete-time error dynamics of UAV leader–follower models are analyzed. Next, a linear quadratic optimization problem is formulated with the objective of minimizing the errors between the desired and actual states consisting of velocity and position information of the follower. The optimal formation tracking problem of near-equilibrium cases is addressed by using a backward recursion method, and then the results are further extended to the general dynamic case where the leader moves at an uncertain time-varying velocity. Additionally, angle deviations are investigated, and it is proved that the similar state dynamics to the general case can be derived and the principle of control strategy design can be maintained. By using actual real-world data, numerical experiments verify the effectiveness of the proposed optimal UAV formation-tracking algorithm in both near-equilibrium and dynamic control cases in the presence of network-induced delays.     

基于动态阈值匹配追踪的主动声呐直达波抑制方法

双基地声呐中的直达波干扰可以通过重构抵消的方式进行抑制。这种方法需要对直达波信道进行估计,传统的正交匹配追踪算法的收敛速度慢,分步正交匹配追踪等算法在提高收敛速度时牺牲了信道估计精度,导致回波检测能力下降。本文提出一种动态阈值匹配追踪算法估计直达波的信道响应,在提高收敛速度的同时兼顾了信道估计精度。在仿真环境中,达到同样的直达波抑制效果,所提算法与传统正交匹配追踪算法相比,收敛速度显著提升,检测输出的回波强度比分步正交匹配追踪算法高4dB;海试数据处理结果中,所提方法迭代收敛速度较正交匹配追踪算法提升4倍;输出的回波强度比分步正交匹配追踪算法高2dB。     

一种基于时空变换和压缩感知的磁共振螺旋采样的图像重建算法

螺旋采样磁共振快速成像在功能性成像、并行成像和动态成像等领域发挥着越来越重要的作用.螺旋采样图像重建的传统算法是用核函数将螺旋状分布的k空间数据插值到均匀网格中,再利用傅里叶变换和最小二乘法进行重建.但是基于网格化的算法对核函数过于依赖,在网格化过程中产生难以避免的误差.该文提出了基于时空变换和压缩感知的l1范数的最优化模型和重建算法.时空变换矩阵描述了空间上的磁共振图像与采集到的时域信号间的关系,使得算法直接使用采集到的数据作为保真约束项,避免了网格化过程产生的误差.此外,基于图像处理单元的并行计算被用来提高时空变换矩阵的运算速度,使得算法具有较强的应用价值.     

Vertex centrality of complex networks based on joint nonnegative matrix factorization and graph embedding

Finding crucial vertices is a key problem for improving the reliability and ensuring the effective operation of networks, solved by approaches based on multiple attribute decision that suffer from ignoring the correlation among each attribute or the heterogeneity between attribute and structure. To overcome these problems, a novel vertex centrality approach, called VCJG, is proposed based on joint nonnegative matrix factorization and graph embedding. The potential attributes with linearly independent and the structure information are captured automatically in light of nonnegative matrix factorization for factorizing the weighted adjacent matrix and the structure matrix, which is generated by graph embedding. And the smoothness strategy is applied to eliminate the heterogeneity between attributes and structure by joint nonnegative matrix factorization. Then VCJG integrates the above steps to formulate an overall objective function, and obtain the ultimately potential attributes fused the structure information of network through optimizing the objective function. Finally, the attributes are combined with neighborhood rules to evaluate vertex's importance. Through comparative analyses with experiments on nine real-world networks, we demonstrate that the proposed approach outperforms nine state-of-the-art algorithms for identification of vital vertices with respect to correlation, monotonicity and accuracy of top-10 vertices ranking.     

基于联合平行投影迭代的叠栅层析重建

描述了一种新的叠栅层析代数迭代模型,并针对传统代数迭代法中的垂直投影算法收敛速度较慢的问题,结合新模型提出了一种改进了的平行投影重建算法.用该算法进行了数值模拟重建,结果表明：与叠栅层析中的变换类算法相比,对非完全数据问题,新算法具有有效结合先验知识进行重建的能力;与传统的垂直投影算法相比,新算法能在保证重建准确度的前提下大幅度的提高收敛速度.     

Creep and shrinkage effect on the dynamic analysis of reinforced concrete slab-and-beam structures

In this paper, a solution to the dynamic problem of reinforced concrete slab-and-beam structures including creep and shrinkage effects is presented. The adopted model takes into account the resulting in-plane forces and deformations of the plate as well as the axial forces and deformations of the beam, due to the combined response of the system. The analysis consists of isolating the beams from the plate by sections parallel to the lower outer surface of the plate. The influence on creep and shrinkage effects of the time between the casting and the loading of the plate and the beams is taken into account. A lumped mass matrix is constructed from the tributary mass areas to the nodal mass points and a stiffness matrix is computed using the solution of the corresponding static problem. Both free and forced vibrations are considered and numerical examples of practical interest are presented. The discrepancy between the eigenvalues obtained using the present analysis, which better approximates to the actual response of the plate-beam system and the corresponding ones which ignore the in-plane forces and deformations requires the adopted model.     

A NOVEL TECHNIQUE FOR INVERSE IDENTIFICATION OF DISTRIBUTED STIFFNESS FACTOR IN STRUCTURES

A computational inverse technique for identifying stiffness distribution in structures is proposed in this paper using structural dynamics response in the frequency domain. In the present technique, element stiffness factors of the finite element model of a structure are taken to be the parameters, and explicitly expressed in a linear form in the system equation for forward analysis of the harmonic response of the structure. This offers great convenience in applying Newton's method to search for the parameters of stiffness factor inversely, as the Jacobian matrix can be obtained simply by solving sets of linear algebraic equation derived from the system equation. Examples of identifying stiffness factor distribution which is often related to damage in the elements of the structure are presented to demonstrate the present technique. The advantages of the present technique for inverse parameter identification problem are (1) the number of the parameters can be very large; (2) the identification process is very fast and (3) the accuracy is very high. The efficiency of the proposed technique is compared with genetic algorithms.     

A new adaptive observer-based synchronization scheme for private communication

The problem of secure communication via parameter modulation in a class of uncertain chaotic systems is considered. For a given uncertain master chaotic system, a robust adaptive observer-based response can be constructed to synchronize the drive system. The information signal is used to modulate one parameter of a given chaotic system. The resulting chaotic signal is later demodulated and the information signal is recovered using an adaptive demodulator. The convergence of the demodulator is established. Theoretical analysis and numerical simulation on Chua's circuit show the effectiveness and efficiency of the proposed scheme.     

Calculating frequency response functions for uncertain systems using complex affine analysis

This paper is concerned with the effect of parametric uncertainty upon the response of mechanical systems. Two uncertainty propagation techniques are employed and compared against a benchmark based upon randomly scanning input parameter ranges. The first technique, complex interval analysis, is computationally very efficient but suffers from the issue of dependency which may result in large overestimation of the system response. The second technique, namely complex affine analysis, is presented here for the first time and it keeps track of variable dependencies throughout the calculation thus limiting overestimation, albeit at some computational expense. The methods are demonstrated on the problem of calculation of the frequency response functions of a simple lumped mass system with uncertain parameters for purposes of transparency of the presented ideas, although these ideas are equally applicable to more complex systems. It transpired that the complex affine analysis performed significantly better than its interval counterpart.     

Analysis of static and dynamic structural problems by a combined finite element-transfer matrix method

The combined use of the finite element and transfer matrix techniques (FETM) for the study of dynamic problems was proposed a few years ago, in order to overcome the large amount of computer storage and long computation time that the finite element technique often requires. In this paper some interesting applications are emphasized for both static and dynamic problems of structures. A great deal of attention has been paid to the use of shell isoparametric elements for very thin structures, where the usual numerical integration by a two-by-two Gaussian quadrature of the stiffness matrix leads to an ineffective increase of stiffness in the structure. Particularly appealing seems to be the use of quadratic shell elements in the FETM method, because even with a reduction in the total number of elements of the structure it is possible to increase the accuracy of results. Computation time is appreciably reduced by this method, because of the notable lowering of the final matrix order, the manipulation of which gives the solution of the problem. Some results for natural frequencies of a thin plate are finally presented, showing a favourable agreement with those obtained by other proposed methods.     

Novel global robust stability criteria for interval neural networks with multiple time-varying delays

This Letter is concerned with the problem of robust stability analysis for interval neural networks with multiple time-varying delays and parameter uncertainties. The parameter uncertainties are assumed to be bounded in given compact sets and the activation functions are supposed to be bounded and globally Lipschitz continuous. A sufficient condition is obtained by means of Lyapunov functionals, which guarantees the existence, uniqueness and global asymptotic stability of the delayed neural network for all admissible uncertainties. This condition is in terms of a linear matrix inequality (LMI), which can be easily checked by using recently developed algorithms in solving LMIs. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method.     

Impact load identification of composite structure using genetic algorithms

For structural health monitoring of composite structure, it is important to quickly and accurately identify the impact load whenever an impact event occurs. This paper proposes a genetic algorithms (GA)-based approach for impact load identification, which can identify the impact location and reconstruct the impact force history simultaneously. In this study, impact load is represented by a set of parameters, thus the impact load identification problem in both space (impact location) and time (impact force history) domains is transformed to a parameter identification problem. A forward model characterizes the dynamic response of the structure subject to a known impact force is incorporated in the identification procedure. By minimizing the difference between the analytical responses given by the forward model and the measured ones, GA adaptively identify the impact location and force history with its global search capability. This new impact identification approach is applied to a stiffened composite panel. The stiffened composite panel is modeled as an equivalent laminate with varying properties and the forward response is obtained by using an assumed modes approach. To improve the computational efficiency, micro-GA (μGA) is employed to perform the identification task. Numerical simulation studies are conducted to demonstrate the effectiveness and applicability of the proposed method.