一个新的特征选择判据——不确定性系数

提出了运用特征子集的不确定性系数作为特征选择的度量。特征子集的不确定性系数是一种单调的特征子集信息度量，因此可以将它作为特征选择度量。实验表明，特征子集的不确定性系数作为特征选择度量是合理和可行的。

专家质疑评估混合物的不确定性系数

权威混合物毒理学专家认为，不能假定在评估对单独化学物质的暴露构成的健康风险时通常使用的缺省不确定性系数，以免遭受化学混合物的潜在有害影响。

具有结构不确定性系统的鲁棒H_∞控制

本文研究具有结构不确定性系统的鲁棒H∞状态反馈控制问题，这个问题的解涉及到一个代数Riccati方程．通过分析，这个问题的解与一个辅助的线性时不变系统的H∞状态反馈控制问题的解是等价的．把这一结果用于求解具有结构不确定性系统的鲁棒H∞动态输出反馈控制问题，很方便地给出只需求解两个代数Riccati方程的鲁棒H∞动态输出反馈控制问题的解．

统计模型的“不确定性”问题与倾向值方法

量化社会学研究往往基于特定的统计模型展开。近十几年来日益流行的倾向值方法也不例外,其在实施过程中需要同时拟合估计倾向值得分的"倾向值模型"与估计因果关系的"结果模型"。然而,无论是其模型形式还是系数估计,统计模型本身都具有不可忽视的"不确定性"问题。本研究在倾向值分析方法的框架下,系统梳理和阐释了模型形式不确定性与模型系数不确定性的内涵及其处理方法。通过分析"蒙特卡洛模拟"数据与经验调查数据,本文展示了在使用倾向值方法进行因果估计的过程中,研究者如何通过"贝叶斯平均法"进行多个备选倾向值模型的选择,以及如何通过联合估计解决倾向值模型与估计模型中的系数不确定性问题。本文的研究也表明,在考虑倾向值估计过程的不确定性之后,结果模型中对于因果关系的估计呈现更小的置信区间和更高的统计效率。

区间数直觉模糊多属性决策的联系数新算法

针对区间直觉模糊多属性决策的模糊不确定问题,提出一种基于联系数的区间直觉模糊多属性决策新算法。首先把区间数转换成a+bi型的二元联系数,把区间直觉模糊数转换为a+bi形式的直觉模糊数;再参照三元联系数的势函数概念计算直觉模糊数的直觉模糊势,建立基于直觉模糊势的多属性决策模型,依据模型中的综合加权直觉势大小得出n个方案的初排序,依据模型中的综合加权模糊势做初排序的不确定性分析得到终排序。实例应用结果证实了新算法思路的合理性和结果的有效性。

三元联系数的一阶全偏联系数中i取值的研究

三元联系数的一阶全偏联系数是揭示三元联系数所刻画的系统状态在一阶微观层次上演化趋势的一个重要数学工具.针对现有的一阶全偏联系数算法的不足,系统从“正常”到“失效”两个极态的状态刻画为例阐述改进算法所依据的物理原理,并举实例说明应用.

一阶全偏联系数的计值公式及其应用

偏联系数揭示联系数刻画的系统状态在微观层次上的演化趋势。针对现有三元联系数的一阶全偏联系数数值计算受不确定性示性系数i取值不确定的困扰,给出了一个新的三元联系数的一阶全偏联系数计值公式,用系统可靠性理论中系统“正常”与“失效”两个极端态的叠加为例阐述该计值公式的原理,实例说明本文给出的算法有效可靠。

一种基于粗糙集启发式的特征选择算法

本文基于粗糙集中关于非精确集和精确集理论思想,提出了一个新的特征度量指标,即相对互信息比RMI,由此,设计了一种基于粗糙集的启发式特征选择算法MRMI-UC。首先利用可辨识矩阵,计算出条件属性相对于决策属性的核,以核形成当前候选特征子集作为基准点,以最大化相对互信息和不确定性系数为原则,筛选剩余特征。通过对比实验,结果表明,本文提出的算法在多数情况下能够得到较优的特征子集,算法是有效的,切实可行的。

风险利益度量方法的探索

伴随现代经济的发展,经济活动中的风险利益便成为普遍存在的经济现象。本文对风险利益问题作了量化分析,提出了风险利益度量的四种方法,并认为探索风险利益度量方法对于风险利益活动的决策具有重要意义。

ROBUST CONTROL OF A CLASS OF NONLINEAR SYSTEM WITH TIME-VARYING PAR AMETRIC UNCERTAINTIES

A class of triangular non li near system with disturbances which has unknown multiplicative time varying par ametric uncertainties in each virtual control is treated by a backstepping techn ique. The controller designed for all admissible uncertainties can guarantee tha t all states of its closed loop system are uniformly bounded. The robust contro ller design algorithm and a sufficient condition of the system stability are giv en. In addition, the closed loop system has an ISS property when the multiplica tive time varying parametric uncertainties are viewed as inputs to the system. Thus, this design provides a way to prevent a destabilizing effect of the multip licative time varying parametric uncertainties. Finally, simulational example i s given and simulational result shows that the controller exhibits effectiveness and excellent robustness.

Design for robust stabilization of nonlinear systems with uncertain parameters

Based on Lyapunov stability theory, a design method for the robust stabilization problem of a class of nonlinear systems with uncertain parameters is presented. The design procedure is divided into two steps: the first is to design controllers for the nominal system and make the system asymptotically stabi1ize at the expected equilibrium point; the second is to construct closed-loop nominal system based on the first step, then design robust controller to make the error of state between the origina1 system and the nominal system converge to zero, thereby a dynamic controller with the constructed closed-loop nominal system served as interior dynamic is obtained. A numerical simulation verifies the correctness of the design method.

Robust H_∞ directional control for a sampled-data autonomous airship

A robust H∞ directional controller for a sampled-data autonomous airship with polytopic parameter uncertainties was proposed. By input delay approach, the linearized airship model was transformed into a continuous-time system with time-varying delay. Sufficient conditions were then established based on the constructed Lyapunov-Krasovskii functional, which guarantee that the system is mean-square exponentially stable with H∞ performance. The desired controller can be obtained by solving the obtained conditions. Simulation results show that guaranteed minimum H∞ performance γ=1.4037 and fast response of attitude for sampled-data autonomous airship are achieved in spite of the existence of parameter uncertainties.

Sliding mode identifier for parameter uncertain nonlinear dynamic systems with nonlinear input

This paper presents a sliding mode (SM) based identifier to deal with the parameter identification problem for a class of parameter uncertain nonlinear dynamic systems with input nonlinearity. A sliding mode controller (SMC) is used to ensure the global reaching condition of the sliding mode for the nonlinear system; an identifier is designed to identify the uncertain parameter of the nonlinear system. A numerical example is studied to show the feasibility of the SM controller and the asymptotical convergence of the identifier.

Probabilistic model and analysis of coupled train-ballasted track-subgrade system with uncertain structural parameters

Random dynamic responses caused by the uncertainty of structural parameters of the coupled train-ballasted track-subgrade system under train loading can pose safety concerns to the train operation.This paper introduced a computational model for analyzing probabilistic dynamic responses of three-dimensional(3D)coupled train-ballasted track-subgrade system(TBTSS),where the coupling effects of uncertain rail irregularities,stiffness and damping properties of ballast and subgrade layers were simultaneously considered.The number theoretical method(NTM)was employed to design discrete points for the multi-dimensional stochastic parameters.The time-histories of stochastic dynamic vibrations of the TBSS with systematically uncertain structural parameters were calculated accurately and efficiently by employing the probability density evolution method(PDEM).The model-predicted results were consistent with those by the Monte Carlo simulation method.A sensitivity study was performed to assess the relative importance of those uncertain structural parameters,based on which a case study was presented to explore the stochastic probability evolution mechanism of such train-ballasted track-subgrade system.

On exponential stability for systems with state delays

This paper considers the issue of delay-dependent exponential stability for time-delay systems. Both nominal and uncertain systems are investigated. New sufficient conditions in terms of linear matrix inequalities(LMIs) are obtained. These criteria are simple owing to the use of an integral inequality. The model transformation approaches,bounding techniques for cross terms and slack matrices are all avoided in the derivation. Rigorous proof and numerical examples showed that the proposed criteria and those based on introducing slack matrices are equivalent.

Uncertainty Calculation of Roundness Assessment by Automatic Differentiation in Coordinate Metrology

Reomtly, Coordinate bieasuring Machines （CMMs） are widely used to measure roundness errors. Roundness is calculated from a large number of points collected from the profiles of the parts. According to the Guide to the Expression of Uncertainty in Measta- meat （GUM）, all measurement results must have a stated uncertainty associated the titan. However, no CMMs give the uncertainty value of the roundness, because no suitable measrement uncertainty calculation procedure exists. In the case of roundness raeasurement in coordinate metrology, this paper suggests the algorithms for the calculation of the measurement uncertainty of the roudness deviation based on the two mainly used association criteria, LSC and MZC. The calculation of the sensitivity coefficients for the uncertainty calculatiion can be done by autnatic differentiation, in order to avoid introducing additional emars by the traditional difference quotient approxima- tions. The proposed methods are exact and need input data only as the nrasured coordinates of the data points and their associated un- certainties.

Consistency and Asymptotic Property of a Weighted Least Squares Method for Networked Control Systems

In this paper, we study the problems related to parameter estimation of a single-input and single-output networked control system, which contains possible network-induced delays and packet dropout in both of sensor-to-controller path and controller-to-actuator path. A weighted least squares(WLS) method is designed to estimate the parameters of plant, which could overcome the data uncertainty problem caused by delays and dropout. This WLS method is proved to be consistent and has a good asymptotic property. Simulation examples are given to validate the results.

Direct adaptive control for lane keeping in intelligent vehicle systems

In this paper, with parametric uncertainties such as the mass of vehicle, the inertia of vehicle about vertical axis, and the tire cornering stiffness, we deal with the vehicle lateral control problem in intelligent vehicle systems. Based on the dynamical model of vehicle, by applying Lyapunov function method, the control problem for lane keeping in the presence of parametric uncertainty is studied, the direct adaptive algorithm to compensate for parametric variations is proposed and the terminal sliding mode variable structure control laws are designed with look-ahead references systems. The stability of the system is investigated from the zero dynamics analysis. Simulation results show that convergence rates of the lateral displacement error, yaw angle error and slid angle are fast.

Synchronization of hyperchaotic Rossler system with uncertain parameters via nonlinear control

Based on the Lyapunov stability theory,a new method for synchronization of hyperchaotic Rossler system with uncertain parameters is proposed. By this method, choosing appropriate control law and adaptive update law of uncertain parameters, all the errors of system variable synchronization and of uncertain param- eter track are asymptotically stable. The theoretical analysis and the numerical simulations prove the efffectiveness of the oroDosed method.

Guaranteed cost sampled-data control for uncertain nonlinear time-varying delay system

The robust guaranteed cost sampled-data control was studied for a class of uncertain nonlinear systems with time-varying delay. The parameter uncertainties are time-varying norm-bounded and appear in both the state and the input control matrices. By applying an input delay approach, the system was transformed into a continuous time-delay system. Attention was focused on the design of a robust guaranteed cost sampled-data control law which guarantees that the closed-loop system is asymptotically stable and the quadratic performance index is less than a certain bound for all admissible uncertainties. By applying Lyapunov stability theory, the theorems were derived to provide sufficient conditions for the existence of robust guaranteed cost sampled-data control law in the form of linear matrix inequalities (LMIs), especially an optimal state-feedback guaranteed cost sampled-data control law which ensures the minimization of the guaranteed cost was given. The effectiveness of the proposed method was illustrated by a simulation example with the asymptotically stable curves of system state under the initial condition of x(0)=[0.679 6 0].