Aeroelastic tailoring using fiber orientation and topology optimization

This work presents a structural optimization aided design methodology for composite laminated plates subject to fluid-structure interaction. The goal of the optimization procedure is to increase the flutter speed onset through the maximization of natural frequencies related to the vibration modes involved in the phenomenon. The aeroelastic stability analysis is performed using ZAERO software system, which includes ZONA 6 unsteady lifting surface method. The finite element method is applied to solve the structural model equilibrium equations, the eigenvalues sensitivities with respect to design variables are calculated analytically, and sequential linear programming is applied. The maximization is accomplished using two methods; the first method uses an aeroelastic analysis to determine which eigenmode causes the flutter onset, and its eigenvalue is then maximized. In the second method, a forward finite difference method is applied and the flutter speed sensitivities with respect to the eigenvalues are calculated. This sensitivity is used to guide the optimization process. Finally, a topology optimization problem is formulated to reduce the plate mass under a minimum flutter velocity constraint, using density distribution as the design variable.     

Multiple robust H∞ controller design using the nonsmooth optimization method

This paper proposes a systematic technique to design multiple robust H_∞ controllers. The proposed technique achieves a desired robust performance objective, which is impossible to achieve with a single robust controller, by dividing the uncertainty set into several subsets and by designing a robust controller to each subset. To achieve this goal with a small number of divisions of the uncertainty set, an optimization problem is formulated. Since the cost function of this optimization problem is not a smooth function, a numerical nonsmooth optimization algorithm is proposed to solve this problem. This method avoids the use of Lyapunov variables, and therefore it leads to a moderate size optimization problem. A numerical example shows that the proposed multiple robust control method can improve the closed‐loop performance when a single robust controller cannot achieve satisfactory performance. Copyright © 2009 John Wiley & Sons, Ltd.     

Multipurpose controller design using parametric optimization with dynamic constraints

A systematic and effective design procedure for a class of linear multivariable feedback control systems is proposed For simultaneously achieving robust tracking of the prescribed input signal via the Q-parametrization approach and internal model principle, the prescribed transient specifications by choosing an appropriate performance criterion, robust stabilization, and sensitivity minimization. The problem can best be cast in the form of an optimization problem with dynamic constraints. A numerical method is formulated to solve the optimization problem with dynamic constraints using a non-linear programming method. A numerical example is provided to illustrate the main results of the paper.     

基于目标优化的高光谱图像亚像元定位

目的 高光谱图像混合像元的普遍存在使得传统的分类技术难以准确确定地物空间分布,亚像元定位技术是解决该问题的有效手段。针对连通区域存在孤立点或孤立两点等特例时,通过链码长度求周长最小无法保证最优结果及优化过程计算量大的问题,提出了一种改进的高光谱图像亚像元定位方法。方法 以光谱解混结合二进制粒子群优化构建算法框架,根据光谱解混结果近似估计每个像元对应的亚像元组成,通过分析连通区域存在特例时基于链码长度求周长最小无法保证结果最优的原因,提出修改孤立区域的周长并考虑连通区域个数构造代价函数,最后利用二进制粒子群优化实现亚像元定位。为了减少算法的时间复杂度,根据地物空间分布特点,采用局部分析代替全局分析,提出了新的迭代优化策略。结果 相比直接基于链码长度求周长最小的优化结果,基于改进的目标函数优化后,大部分区域边界更明显,并且没有孤立1点和孤立两点的区域,识别率可以提高2%以上,Kappa系数增加0.05以上,新的优化策略可以使算法运算时间减少近一半。结论 实验结果表明,本文方法能有效提高亚像元定位精度,同时降低时间复杂度。因为高光谱图像中均匀混合区域不同地物的分布空间相关性不强,因此本文方法适用于非均匀混合的高光谱图像的亚像元定位。     

AN ITERATIVE LMI APPROACH TO RFDF FOR LINEAR SYSTEM WITH TIME‐VARYING DELAYS

This paper deals with robust fault detection filter (RFDF) problem for a class of linear uncertain systems with time‐varying delays and model uncertainties. The RFDF design problem is formulated as an optimization problem by using L₂‐induced norm to represent the robustness of residual to unknown inputs and modelling errors, and the sensitivity to faults. A sufficient condition to the solvability of formulated problem is established in terms of certain matrix inequalities, which can be solved with the aid of an iterative linear matrix inequality (ILMI) algorithm. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.     

Preconditioning technique for symmetric M-matrices

Abstract Linear systems with M-matrices occur in a wide variety of areas including numerical partial differential equations, input-output production and growth models in economics, linear complementarity problems in operations research and Markov chains in stochastic analysis.In this paper, we propose a new preconditioner for solving a system with symmetric positive definite M-matrix by the preconditioned conjugate gradient (PCG) method. We show that our preconditioner increases the convergence rate of the PCG method and reduces the operation cost. Numerical results are given.     

Investigation and optimization of wave processes in inhomogeneous media with impedance boundary

The problem of numerical modeling and optimization of wave processes in inhomogeneous media with impedance boundary for parabolic Schrödinger-type wave equation is considered. The optimality criterion is formulated, differential properties of the optimization problem are analyzed, and a numerical method is proposed to model and optimize acoustic fields in inhomogeneous media.     

The steady-state region of attraction under linear feedback control: A numerical approach

In this paper, a numerical approach to operability analysis is developed. Based on the concept of the steady-state region of attraction, which indicates the initial operating conditions that can be driven to a given setpoint, this analysis helps design engineers assess whether a process can be effectively controlled by linear control systems. Using steady-state operating data that are generated with process simulators (such as ASPEN PLUS^®), the steady-state region of attraction are calculated by solving the proposed constrained nonlinear optimization problem. The objective function for the optimization problem is developed using the ellipsoid theory while the constraint functions are formulated from the complement set of the initially defined constraint set and the boundary of the available input space (AIS). Furthermore, as the solution of a nonlinear optimization problem generally depends on the initial starting point, a method of generating a set of ellipsoids in the hyperspace to start the calculation is also developed. The proposed constrained nonlinear optimization problem can be solved using numerical tools such as MATLAB^®. This analysis can be performed based on process flowsheets with process simulators and thus is useful in early stages of process design. The use of the proposed numerical framework is illustrated by a case study of a methyl acetate reactive distillation column.     

Optimum design of prestressed concrete beams using constrained differential evolution algorithm

This paper is concerned with the cost minimization of prestressed concrete beams using a special differential evolution-based technique. The optimum design is posed as single-objective optimization problem in presence of constraints formulated in accordance with the current European building code. The design variables include geometrical dimensions that define the shape of the cross section and the amount of prestressing steel. A special (μ?+?λ)-constrained differential evolution method is performed in order to solve the optimization problem. Its search mechanism depends on several mutation strategies whereas an archiving-based adaptive tradeoff model is in charge of selecting a specific constraint-handling technique. Finally, numerical examples are included to illustrate the application of the presented approach.     

Modeling and analysis for multi-period, multi-product and multi-resource production scheduling

This study presents a framework for solving the multi-period, multi-product and multi-resource production-scheduling (M³PS) problem. Practically, the main concern for an M³PS problem is how to satisfy two management policies: (1) each product is manufactured in a continuous manner so that once the product is on a production line, it will complete its production procedure without interruption, and (2) the number of the product's types is limited during one period. By defining the decision variables and taking into account the machine's capacity and the customers' demand, a mixed integer programming (MIP) Model is formulated. To solve this MIP problem, a two-phase approach is proposed. In phase 1, the search space of the MIP Model is transformed into a preliminary pattern by a heuristic mining algorithm so that a hyper assignment problem can be formed as a reference model to be solved. In phase 2, a stochastic global optimization procedure that incorporates a genetic algorithm with neighborhood search techniques is designed to obtain the optimal solution. A numerical experiment is presented with an illustration, and it shows that the proposed model is adequate to cope with complicate scheduling problems.     

An efficient method for computing leading eigenvalues and eigenvectors of large asymmetric matrices

An efficient method for computing a given number of leading eigenvalues (i.e., having largest real parts) and the corresponding eigenvectors of a large asymmetric matrixM is presented. The method consists of three main steps. The first is a filtering process in which the equationx = Mx is solved for an arbitrary initial conditionx(0) yielding:x(t)=e ^Mt x(0). The second step is the construction of (n+1) linearly independent vectorsv _m =M ^m x, 0mn orv _m =e ^mMt x ( being a short time interval). By construction, the vectorsv _m are combinations of only a small number of leading eigenvectors ofM. The third step consists of an analysis of the vectors {v _m } that yields the eigenvalues and eigenvectors. The proposed method has been successfully tested on several systems. Here we present results pertaining to the Orr-Sommerfeld equation. The method should be useful for many computations in which present methods are too slow or necessitate excessive memory. In particular, we believe it is well suited for hydrodynamic and mechanical stability investigations.     

视觉信息损失先验的图像分层去雾方法

目的 针对自然场景下含雾图像呈现出低对比度和色彩失真的问题,提出一种基于视觉信息损失先验的图像去雾算法,将透射图预估转化成求解信息损失函数最小值的目标规划问题。方法 首先通过输入图像的视觉特性将图像划分成含雾浓度不同的3个视觉区域。然后根据含雾图像的视觉先验知识构造视觉信息损失函数,通过像素值溢出映射规律对透射率取值范围进行约束,采用随机梯度下降法求解局部最小透射率图。最后将细化后的全局透射率图代入大气散射模型求解去雾结果。结果 结合现有的典型去雾算法进行仿真实验,本文算法能够有效地复原退化场景的对比度和清晰度,相比于传统算法,本文算法在算法实时性方面提升约20%。结论 本文算法在改善中、浓雾区域去雾效果的同时,提升了透射图预估的效率,对改善雾霾天气下视觉成像系统的能见度和鲁棒性具有重要意义。     

Parameter dependent H∞ control by finite dimensional LMI optimization: application to trade‐off dependent control

In this paper, we consider the design of an H_∞ trade‐off dependent controller, that is, a controller such that, for a given Linear Time‐Invariant plant, a set of performance trade‐offs parameterized by a scalar θ is satisfied. The controller state space matrices are explicit functions of θ. This new problem is a special case of the design of a parameter dependent controller for a parameter dependent plant, which has many application in Automatic Control. This last design problem can be naturally formulated as a convex but infinite dimensional optimization problem involving parameter dependent Linear Matrix Inequality (LMI) constraints. In this paper, we propose finite dimensional (parameter independent) LMI constraints which are equivalent to the parameter dependent LMI constraints. The parameter dependent controller design is then formulated as a convex finite dimensional LMI optimization problem. The obtained result is then applied to the trade‐off dependent controller design. A numerical example emphasizes the strong interest of our finite dimensional optimization problem with respect to the trade‐off dependent control application. Copyright © 2005 John Wiley & Sons, Ltd.     

On the efficient and accurate solution of the skew-symmetric eigenvalue problem: An arrangement of new and already known algorithmic formulations

Algorithms are presented to solve the special eigenvalue problem $\text{AZ}\text{=}\text{Zλ}$, where $\text{A}$ is skew-symmetric. The effective use of Householder's method, the bisection method and inverse iteration for solving the complete eigen-value problem are described in some detail. Simultaneous vector iteration is formulated for skew-symmetric matrices. The amount of work for the skew-symmetric Jacobi algorithm and the simultaneous vector iteration may be reduced by using the solution of a simplified eigenvalue problem. For Hermitian matrices also quadratic eigenvalue bounds for groups of eigenvalues and linear bounds for groups of eigenvectors are derived. The case where the set of calculated eigenvectors is not orthonormal is considered in some detail. In principle, the skew-symmetric eigenvalue problem may be easily transformed into a symmetric eigenvalue problem; but such a procedure has the following disadvantages: first, the results are in general less accurate, and, second, the eigenvectors which belong to well separated eigenvalues are not uniquely determined.     

A Parameter Dependent Controller Design Approach for Delayed LPV System

This paper investigates the memory state feedback controller synthesis problem for linear parameter‐varying (LPV) systems with time‐varying input delay. A novel state transformation is proposed to reduce the influence of time delay, and two types of Lyapunov‐Krasovskii functional are employed to guarantee the stability of the closed‐loop system and induced L₂ norm performance. The controller gain is formulated to parameter dependent, and design method is then led to a convex optimization problem and solved by parameter gridding technique. A numerical example is provided to validate the effectiveness of the proposed approach.     

Topology optimization of freely vibrating continuum structures based on nonsmooth optimization

The non-differentiability of repeated eigenvalues is one of the key difficulties to obtain the optimal solution in the topology optimization of freely vibrating continuum structures. In this paper, the bundle method, which is a very promising one in the nonsmooth optimization algorithm family, is proposed and implemented to solve the problem of eigenfrequency optimization of continuum. The bundle method is well-known in the mathematical programming community, but has never been used to solve the problems of topology optimization of continuum structures with respect to simple or multiple eigenfrequencies. The advantage of this method is that the specified information of iteration history may be collected and utilized in a very efficient manner to ensure that the next stability center is closer to the optimal solution, so as to avoid the numerical oscillation in the iteration history. Moreover, in the present method, both the simple and multiple eigenfrequencies can be managed within a unified computational scheme. Several numerical examples are tested to validate the proposed method. Comparisons with nonlinear semidefinite programming method and 0–1 formulation based heuristic method show the advantages of the proposed method. It is showed that, the method can deal with the nonsmoothness of the repeated eigenvalues in topology optimization in a very effective and efficient manner without evaluating the multiplicity of the eigenvalues.     

马尔可夫跳变系统的鲁棒故障检测与时域优化

研究马尔可夫跳变系统(MJS) 鲁棒故障检测滤波器(FDF) 的设计与优化问题. 基于观测器构建残差发生器, 将相应的FDF 设计问题转化为H_∞ 滤波问题, 以LMI 的形式得到并证明了FDF 存在的充分条件及求解方法. 为进一步改善故障检测系统的性能, 采用一种时域优化方法对其进行优化, 并以矩阵Moore-Penrose 逆的形式给出了该优化问题的最优解. 数值仿真表明该方法具有较好的检测效果.     

An M-Stage System with Indeterminate Processing Time: Schedule Optimization

The M-machine problem with interval job time formulated in Part I is solved by the method of interval logical determinants.     

高分辨率极化SAR图像水平集分割

目的 传统的极化SAR图像分割方法中,由于采用的统计分布模型不能较好地描述高分辨率的图像纹理特征,导致高分辨率极化SAR图像分割效果较差。针对这个问题,本文将具有广泛适用性的KummerU分布嵌入到水平集极化SAR图像分割方法中,提出了一种新的极化SAR图像分割算法。方法 将KummerU分布作为高分辨率极化SAR图像的统计模型,定义一种适用于极化SAR图像分割的能量泛函;利用最大似然法对各个区域的KummerU分布进行参数估计,并通过数值偏微分方程的方法求解水平集函数,实现极化SAR图像的区域分割。结果 分别对仿真全极化数据,真实全极化数据进行分割实验,结果表明本文提出的方法其分割精度高于传统方法,分割精度高于95%,从而验证了新方法的有效性。结论 本文算法能够对各向同质区和各向异质区的极化SAR图像都能取得良好的分割效果,并适应于多种场景,有效地分割出背景和目标。