一种新的稳健波束形成算法及其一维搜索策略

存在条件失配时自适应波束形成器的性能急剧下降,凸优化技术的引入使稳健波束形成器的设计更加灵活,但同时带来了计算复杂度的增加和工程实现上的困难.针对上述问题,提出了一种基于最小二乘估计的稳健波束形成算法,并推导得到一种基于一维搜索的求解方法.首先利用广义旁瓣对消器的结构将标准Capon波束形成器转化为稳健最小二乘问题,并将该问题转化为二阶锥规划的形式.为了减少计算量,利用二阶锥规划问题的原始问题和对偶问题的关系,将求解过程转化为一维搜索,并利用牛顿迭代法获得最优解,从而获得与标准Capon波束形成相近的计算复杂度.仿真分析表明,该算法具有良好的抗导向矢量失配和快拍数不足的稳健性.     

FINITE ELEMENT MODELING AND ROBUST VIBRATION CONTROL OF TWO-HINGED PLATE USING BONDED PIEZOELECTRIC SENSORS AND ACTUATORS

Active vibration control for a kind of two-hinged plate is developed in this paper. A finite element model for the hinged plate integrated with distributed piezoelectric sensors and actuators is derived, including bending and torsional modes of vibration. In this model, the hinges are simplified as regular plate elements to facilitate operation. The state space representations for bending and torsional vibrations are obtained. Based on two low-order models of the bending and torsional motion, two H ∞ robust controllers are designed for suppressing the vibrations of the bending and torsional modes, respectively. The simulation results indicate the effectiveness and feasibility of the designed H ∞ controllers. The vibration magnitudes of the low-order modes can be reduced without affecting the high frequency modes.     

用鲁棒Riemann求解器和运动重叠网格计算旋翼粘性绕流

发展了一种基于鲁棒Riemann求解器和运动重叠网格技术计算直升机悬停旋翼流场的方法。基于惯性坐标系,悬停旋翼流场是非定常流场,控制方程为可压缩Reynolds平均Navier-Stoke方程,其对流项采用Roe近似Reimann求解器离散,使用改进的五阶加权基本无振荡格式进行高阶重构,非定常时间推进采用含牛顿型LUSGS子迭代的全隐式双时间步方法。为实施旋转运动和便于捕捉尾迹,计算采用运动重叠网格技术。计算得到的桨叶表面压力分布及桨尖涡涡核位置都与实验结果吻合较好。数值结果表明:所发展方法对桨尖涡具有较高的分辨率,对激波具有较好的捕捉能力,该方法可进一步推广到前飞旋翼粘性绕流的计算。     

Using surface‐enhanced Raman scattering (SERS) and fluorescence spectroscopy for screening yeast extracts,a complex component of cell culture media

Yeastolate or yeast extract, which are hydrolysates produced by autolysis of yeast, are often employed as a raw material in the media used for industrial mammalian cell culture. The source and quality of yeastolate can significantly affect cell growth and production; however, analysis of these complex biologically derived materials is not straightforward. The best current method, liquid chromatography–mass spectrometry (LC‐MS), is time‐consuming and requires extensive expertise. This study describes the use of surface‐enhanced Raman scattering (SERS) and fluorescence excitation–emission matrix (EEM) spectroscopy coupled with robust principal component analysis (ROBPCA) for the rapid and facile characterization and discrimination of yeast extracts in aqueous solution. SERS using silver colloids generates time‐dependent signals, where adenine is the strongest contributor, and the spectra are stable and reproducible (< ~3%) at 180 min after mixing. Combining this spectral behavior with chemometric methods enables SERS to be used in discriminating between different yeastolate sources, for assessing lot‐to‐lot variability, and, potentially, to monitor storage‐induced compositional changes. Fluorescence EEM combined with multiway ROBPCA also provides a rapid and inexpensive method for the discrimination of yeastolate, yielding results in terms of sample discrimination very similar to that obtained with SERS. However, the EEM data does not provide the same level of chemical information that is provided by the SERS. Thus, the combination of these two methodologies has the potential to be extremely useful in biopharmaceutical manufacturing, as well as for the rapid characterization and screening of biogenic hydrolysates from animal or plant sources. Copyright © 2011 John Wiley & Sons, Ltd.     

Stability analysis of impulsive delayed switched systems and applications

In this paper, a general class of impulsive delayed switched systems is considered. By employing the Lyapunov–Razumikhin method and some analysis techniques, we established several global asymptotic stability and global exponential stability criteria for the considered impulsive delayed switched systems, which improve and extend some recent works. As an application, the result of global exponential stability are used to study a class of uncertain linear switched systems with time‐varying delays. Several LMI‐based conditions are proposed to guarantee the global robust stability and global exponential stabilization. The designed memoryless state feedback controller can be easily checked by the LMI toolbox in Matlab. Moreover, the dwell time constraint is imposed for the switching law. Finally, two numerical examples and their simulations are given to show the effectiveness of our proposed results. Copyright © 2012 John Wiley & Sons, Ltd.     

A robust optimization model for dynamic market with uncertain production cost

This article presents a robust optimization formulation for dealing with production cost uncertainty in an oligopolistic market scenario. It is not uncommon that players in the market face an equilibrium selling price but uncertain production costs. We show that, based on a nominal problem, the robust optimization formulation can be derived as a variational inequality with control and state variables. This convenient approach may be applied for computing optimal solutions efficiently, which help manufacturers dramatically and rapidly reform production and distribution schedules such that they can compete in the market successfully.     

Support vector machine classifiers with uncertain knowledge sets via robust optimization

In this article we study support vector machine (SVM) classifiers in the face of uncertain knowledge sets and show how data uncertainty in knowledge sets can be treated in SVM classification by employing robust optimization. We present knowledge-based SVM classifiers with uncertain knowledge sets using convex quadratic optimization duality. We show that the knowledge-based SVM, where prior knowledge is in the form of uncertain linear constraints, results in an uncertain convex optimization problem with a set containment constraint. Using a new extension of Farkas' lemma, we reformulate the robust counterpart of the uncertain convex optimization problem in the case of interval uncertainty as a convex quadratic optimization problem. We then reformulate the resulting convex optimization problems as a simple quadratic optimization problem with non-negativity constraints using the Lagrange duality. We obtain the solution of the converted problem by a fixed point iterative algorithm and establish the convergence of the algorithm. We finally present some preliminary results of our computational experiments of the method.     

Derivative-free optimization and neural networks for robust regression

Large outliers break down linear and nonlinear regression models. Robust regression methods allow one to filter out the outliers when building a model. By replacing the traditional least squares criterion with the least trimmed squares (LTS) criterion, in which half of data is treated as potential outliers, one can fit accurate regression models to strongly contaminated data. High-breakdown methods have become very well established in linear regression, but have started being applied for non-linear regression only recently. In this work, we examine the problem of fitting artificial neural networks (ANNs) to contaminated data using LTS criterion. We introduce a penalized LTS criterion which prevents unnecessary removal of valid data. Training of ANNs leads to a challenging non-smooth global optimization problem. We compare the efficiency of several derivative-free optimization methods in solving it, and show that our approach identifies the outliers correctly when ANNs are used for nonlinear regression.     

A method of fuzzy preference relation to authorize the worldwide interoperability for microwave access license in Taiwan

This study proposes a preference relation based evaluation framework to help the National Communication Commission (NCC) in Taiwan authorize a worldwide interoperability for microwave access (WiMAX) license under a fuzzy environment where the uncertainty, subjectivity and vagueness are dealt with linguistic variables parameterized by triangular fuzzy numbers. This study applies the fuzzy multi-criteria decision making approach to determine the importance weights of evaluation criteria and consolidate the performance ratings of possible alternatives. Aggregated the evaluators’ opinions toward the criteria and alternatives, the fuzzy preference relation approach is utilized to obtain the non-dominated degree of each alternative for the decision makers to make a final decision. Simultaneously, an empirical case involving sixteen quantitative and fifteen qualitative evaluation criteria, thirteen telecommunication applicants assessed by twelve specialists from various fields of telecommunication industry in Taiwan is solicited to demonstrate the proposed approach.