QUADRATIC REPRESENTATION FOR ROADWAY PROFILE THAT MINIMIZES EARTHWORK COST

Roadway design usually involves choices regarding grade selection and earthwork (transportation) that can be solved using linear programming. Previous work considered the road profile as series of interconnected linear segments. In these models, constraints are included in the linear programming formulation to insure continuity of the road, which cause sharp connectivity points at the intersection of the linear segments. This sharp connectivity needs to be smoothed out after l;he linear programming solution is found and the earth in the smoothed portion of the roadway has to be moved to the landfill. In previous research, the smoothing issue is dealt with after an optimal solution is found. This increases the work required by the design engineer and consequently increases the construction cost; furthermore, the optimal solution is violated by this smoothing operation. In this paper, the issue of sharp connectivity points is resolved by representing the road profile by a quadratic function. The continuit     

Rank-Based Test for Partial Functional Linear Regression Models

This paper investigates the hypothesis test of the parametric component in partial functional linear regression models. Based on a rank score function, the authors develop a rank test using functional principal component analysis, and establish the asymptotic properties of the resulting test under null and local alternative hypotheses. A simulation study shows that the proposed test procedure has good size and power with finite sample sizes. The authors also present an illustration through fitting the Berkeley Growth Data and testing the effect of gender on the height of kids.     

A NEW ALGORITHM FOR PURX O-1 LINEAR PROGRAMS WITH INEQUALITY CONSTRAINTS

ＡＮＥＷＡＬＧＯＲＩＴＨＭＦＯＲＰＵＲＸＯ－１ＬＩＮＥＡＲＰＲＯＧＲＡＭＳＷＩＴＨＩＮＥＱＵＡＬＩＴＹＣＯＮＳＴＲＡＩＮＴＳ￥ＣＨＥＮＪｉａｎｆｅｉ（ＢｉｏｃｈｅｍｉｃａｌＥｎｇｉｎｅｅｒｉｎｇＳｔａｔｅＫｅｙＬａｂｏｒａｔｏｒｙ，Ｂｅｉｊｉｎｇ１０...     

Testing inequality constraints in a linear regression model with spherically symmetric disturbances

This paper develops a Wald statistic for testing the validity of multivariate inequality constraints in linear regression models with spherically symmetric disturbances, and derive the distributions of the test statistic under null and nonnull hypotheses. The power of the test is then discussed. Numerical evaluations are also carried out to examine the power performances of the test for the case in which errors follow a multivariate student-t （Mt） distribution.     

总风险约束的委托组合投资管理激励契约

假设管理者投资组合受总风险约束,通过委托代理模型和数值分析研究委托组合投资管理中基于业绩的线性契约激励效应.研究结论表明: 在总风险约束下,基于业绩的线性契约能激励管理者努力搜集私人信息;风险厌恶的管理者的期望效用和最优努力水平是其收益分享比例的增函数;总风险约束下的管理者的努力水平低于不存在风险约束时的努力水平,风险约束导致管理者信息价值的损失.研究结论从一个侧面解释了委托组合投资管理实务中线性契约被广泛采用的原因,并为私募基金风险管理和契约设计提供参考.     

Consensus control design for multi-agent systems using relative output feedback

This paper studies the consensus problem of multi-agent systems in which all agents are modeled by a general linear system. The authors consider the case where only the relative output feedback between the neighboring agents can be measured. To solve the consensus problem, the authors first construct a static relative output feedback control under some mild constraints on the system model. Then the authors use an observer based approach to design a dynamic relative output feedback control. If the adjacent graph of the system is undirected and connected or directed with a spanning tree, with the proposed control laws, the consensus can be achieved. The authors note that with the observer based approach, some information exchange between the agents is needed unless the associated adjacent graph is completely connected.     

输入受限高超声速飞行器鲁棒变增益控制

针对一个输入受限吸气式高超声速飞行器模型,研究了其鲁棒变增益控制问题。为处理飞行器模型中的建模误差和饱和非线性,将标准的线性变参数（linear parameter-varying, LPV）控制问题扩展到对时变参数、动态不确定性和饱和非线性具有结构摄动的鲁棒性框架内。基于对模型不确定性和饱和非线性的积分二次型约束刻画,以定标线性矩阵不等式（linear matrix inequality, LMI）形式给出其鲁棒变增益控制算法。为进行变增益控制系统设计,建立了飞行器的LPV模型。基于多时间尺度特性,提出了一种由姿态回路和轨迹回路组成的内外环控制结构。内环实现对姿态的严格控制和克服执行机构饱和,外环实现对轨迹的精确跟踪。控制器增益随动压和马赫数调度,实现大跨度机动飞行控制。非线性仿真结果证实了算法和应用的有效性。     

Design of Luenberger function observer with disturbance decoupling for matrix second-order linear systems-a parametric approach

1.INTRODUCTIONThere have been many approaches to disturbance de-couplinginlinear multivariable control systemdesign.Linnemann[1]proposed a numerically stable algorithmfor disturbance decoupling by measurement feedback.Van Der Woude[2]considered the combined problemof disturbance decoupling and stabilization by mea-surement feedback.Syrmos[3]proposed a numericallyefficient algorithm based on Sylvester equations forthe problemof disturbance decoupling with arbitrarypole placement usingstat…     

基于时间切变Gabor原子的时频建模

对尺度高斯函数与线性调频因子卷积,再做频移和时移,得到了具有四个可调参数的时间切变Gabor原子,其时频分布为聚集于其时间中心和频率中心的具有时间倾斜特性的能量曲线。给出了基于该原子集合的频域自适应信号子空间分解和相应的参数自适应时频分布,其中每步分解都采用模拟变焦距过程估计所得原子的四个参数,可用于对非平稳信号中线性和非线性变频成份进行建模和分析。     

A QUANTIFIER-ELIMINATION BASED HEURISTIC FOR AUTOMATICALLY GENERATING INDUCTIVE ASSERTIONS FOR PROGRAMS

A method using quantifier-elimination is proposed for automatically generating programinvariants/inductive assertions.Given a program,inductive assertions,hypothesized as parameterizedformulas in a theory,are associated with program locations.Parameters in inductive assertions arediscovered by generating constraints on parameters by ensuring that an inductive assertion is indeedpreserved by all execution paths leading to the associated location of the program.The method can beused to discover loop invariants-properties of variables that remain invariant at the entry of a loop.Theparameterized formula can be successively refined by considering execution paths one by one;heuristicscan be developed for determining the order in which the paths are considered.Initialization of programvariables as well as the precondition and postcondition,if available,can also be used to further refinethe hypothesized invariant.The method does not depend on the availability of the precondition andpostcondition of a program.Constraints on parameters generated in this way are solved for possiblevalues of parameters.If no solution is possible,this means that an invariant of the hypothesizedform is not likely to exist for the loop under the assumptions/approximations made to generate theassociated verification condition.Otherwise,if the parametric constraints are solvable,then undercertain conditions on methods for generating these constraints,the strongest possible invariant of thehypothesized form can be generated from most general solutions of the parametric constraints.Theapproach is illustrated using the logical languages of conjunction of polynomial equations as well asPresburger arithmetic for expressing assertions.     

Generalized F-test for high dimensional regression coefficients of partially linear models

This paper proposes a test procedure for testing the regression coefficients in high dimensional partially linear models based on the F-statistic. In the partially linear model, the authors first estimate the unknown nonlinear component by some nonparametric methods and then generalize the F-statistic to test the regression coefficients under some regular conditions. During this procedure, the estimation of the nonlinear component brings much challenge to explore the properties of generalized F-test. The authors obtain some asymptotic properties of the generalized F-test in more general cases,including the asymptotic normality and the power of this test with p/n ∈(0, 1) without normality assumption. The asymptotic result is general and by adding some constraint conditions we can obtain the similar conclusions in high dimensional linear models. Through simulation studies, the authors demonstrate good finite-sample performance of the proposed test in comparison with the theoretical results. The practical utility of our method is illustrated by a real data example.     

约束优化问题的一个超线性收敛的广义梯度投影法

对线性约束的非线性优化问题提出了一个新的广义梯度投影法，该算法我们采用了非精确线性搜索，并在每次迭代运算中运用了广义投影矩阵和变尺度方法的思想确定其搜索方向。在通常的假设条件下，证明了算法的整体收敛性和超线性收敛速度。     

Variable feedrate interpolation of NURBS Toolpath with geometric and kinematical constraints for five-axis CNC machining

Variable feedrate interpolation algorithms for five-axis parametric toolpath are very promis- ing but still rather limited currently. In this paper, an off-line feedrate scheduling method of dual NURBS curve is presented with geometric and kinematical constraints. For a given dual parametric curve, the feedrates of sampling points are first scheduled sequent with confined feedrate of cutter tip and machine pivot, chord error, normal acceleration and angular feedrate. Then, the feedrate profiles of angular feed acceleration sensitive regions of the path are adjusted using a bi-directional scanning algorithm. After that, a linear programming method is used to adjust the feedrate profiles of linear feed acceleration sensitive regions and control the linear feed acceleration of both cutter tip and machine pivot within preset values. Further, a NURBS curve is used to fit the feedrates of sampling points. Finally, illustrative examples are carried out to validate the feasibility of the proposed feedrate schedul- ing method. The results show that the proposed method has the ability of effectively controlling the angular feed characters of cutter axis as well as the chord error and linear feed characters of cutter tip and machine pivot, and it has potential to be used in high accuracy and high quality five-axis machining.     

基于特征结构配置的结构主动控制及仿真

考虑了具有最优控制的结构主动控制问题,目的是在系统满足闭环特性的前提下,设计状态反馈控制器使得系统性能泛函极小化。利用特征结构配置方法提供的自由度,给出了性能泛函的显示参数化表示,从而该问题转化为带有约束条件的优化问题,参与优化的变量仅为一组参量。并给出了求解该优化问题的算法,该算法直接基于结构系统矩阵,故其简单性为工程应用提供方便。地震作用下对三层剪切结构建筑模型进行仿真分析,结果表明所提结构主动控制方法的有效性。     

ALLOCATING REPAIRABLE SYSTEM＇S RELIABILITY SUBJECT TO MINIMAL TOTAL COST - AN INTEGER PROGRAMMING APPROACH

Reliability allocation problem is commonly treated using a closed-form expression relating the cost to reliability. A recent approach has introduced the use of discrete integer technique for un-repairable systems. This research addresses the allocation problem for repairable systems. It presents an integer formulation for finding the optimum selection of components based on the integer values of their Mean Time to Failure （MTTF） and Mean Time to Repair （MTTR）. The objective is to minimize the total cost under a system reliability constraint, in addition to other physical constraints. Although, a closed-form expression relating the cost to reliability may not be a linear; however, in this research, the objective function will always be linear regardless of the shape of the equivalent continuous closed-form function. An example is solved using the proposed method and compared with the solution of the continuous closed-form version. The formulation for all possible system configurations, components and subsystems are also considered.     

Asymptotic Properties of Maximum Quasi-Likelihood Estimators in Generalized Linear Models with Diverging Number of Covariates

In this paper, for the generalized linear models (GLMs) with diverging number of covariates, the asymptotic properties of maximum quasi-likelihood estimators (MQLEs) under some regular conditions are developed. The existence, weak convergence and the rate of convergence and asymptotic normality of linear combination of MQLEs and asymptotic distribution of single linear hypothesis test statistics are presented. The results are illustrated by Monte-Carlo simulations.     

Generalized <Emphasis Type="Italic">p</Emphasis>-values for testing regression coefficients in partially linear models

The one-sided and two-sided hypotheses about the parametric component in partially linear model are considered in this paper. Generalized p-values are proposed based on fiducial method for testing the two hypotheses at the presence of nonparametric nuisance parameter. Note that the nonparametric component can be approximated by a linear combination of some known functions, thus, the partially linear model can be approximated by a linear model. Thereby, generalized p-values for a linear model are studied first, and then the results are extended to the situation of partially linear model. Small sample frequency properties are analyzed theoretically. Meanwhile, simulations are conducted to assess the finite sample performance of the tests based on the proposed p-values.     

Robust passive control for discrete-time T-S fuzzy systems with delays

This article deals with the robust stability analysis and passivity of uncertain discrete-time Takagi-Sugeno (T-S) fuzzy systems with time delays. The T-S fuzzy model with parametric uncertainties can approximate nonlinear uncertain systems at any precision. A sufficient condition on the existence of robust passive controller is established based on the Lyapunov stability theory. With the help of linear matrix inequality (LMI) method, robust passive controllers are designed so that the closed-loop system is robust stable and strictly passive.  urthermore, a convex optimization problem with LMI constraints is formulated to design robust passive controllers with the maximum dissipation rate. A numerical example illustrates the validity of the proposed method.     

An Additive-Multiplicative Cox-Aalen Subdistribution Hazard Model for Competing Risks Data

This paper proposes a flexible additive-multiplicative Cox-Aalen hazard model which allows time-varying covariate effects for the subdistribution in a competing risks study. Weighted estimating equation approaches under an covariates-dependent adjusted weight by fitting the Cox proportional hazard model for the censoring distribution are established for inference on the model parametric and nonparametric components. In addition, large number properties are presented and the finite sample behavior of the proposed estimators is evaluated through simulation studies, estimators from the proposed method perform satisfactorily on reduction of the bias. The authors apply our model to a competing risks data set from a tamoxifen trail for breast cancer study.     

Robust model predictive control of continuous uncertain systems*

The authors concern robust model predictive control for linear continuous systems with polytopic uncertainties and input constraints. At each sampling time, a piecewise constant control sequence is obtained by solving a set of linear matrix inequalities. The sufficient conditions on the existence of the model predictive control are given, and the robust stability of the closed-loop systems is guaranteed. A simulation example illustrates the efficiency of the proposed method.