A NEW APPROACH OF SIMULTANEOUS FAULTS DIAGNOSIS BASED ON RANDOM SETS AND DSMT

Simultaneous faults often occur in running equipments, in order to solve the problems of the simultaneous faults, a new approach based on random sets and Dezert-Smarandache Theory (DSmT) is proposed in this paper. Firstly, the simultaneous faults' model is built based on the generalized frame of discernment in DSmT. Secondly, according to the unified description of combination rules in evidence reasoning based on random sets, a new combination rule for simultaneous faults diagnosis is proposed. Thirdly, according to the working characteristics and environment of the sensors used to acquire fault characteristic information, a new method to construct basic probability assignment function is pro- posed based on membership. Finally, diagnosis result is obtained by use of the new combination rule combined with decision rules. A case pertaining to the fault diagnosis for a multi-function rotor test-bed is given, and the result shows that the proposed diagnosis approach is feasible and efficient.

HYBRID FILTER WITH PREDICT-ESTIMATOR AND COMPENSATOR FOR THE LINEAR TIME INVARIANT DELAYED SYSTEM

This paper investigates the problem of real-time estimation for one kind of linear time invariant systems which subject to limited communication capacity. The communication limitations include signal transmission delay, the out-of-sequence measurements and data packet dropout, which appear typically in a network environment. The kernel of filter design is equally to formularize the traditional Kalman filter as one linear weighted summation which is composed of the initial state estimate and all sequential sampled measurements. For it can adapt aforementioned information limitations, the linear weighted summation is then decomposed into two stages. One is a predict-estimator composed by all reached measurements, another is one compensator constructed by those time-delayed data. In the network environment, there are obvious differences between the new hybrid filter and those existing delayed Kalman filters. For example, the novel filter can be optimal in the sense of linear minimum mean square error as soon as all measurements available and has the lowest running time than these existing delayed filters. One simulation, including two cases, is utilized to illustrate the design procedures proposed in this paper.

Input-output approach to robust stability and stabilization for uncertain singular systems with time-varying discrete and distributed delays

Based on input-output approach, the robust stability and stabilization problems for uncertain singular systems with time-varying delays are investigated. The parameter uncertainties are assumed to be norm-bounded and the time-varying delays include both discrete delay and distributed delay. By introducing a new input-output model, the time-delay system is embedded in a family of systems with a forward system without time delay and a dynamical feedback uncertainty. A sufficient and necessary condition, which guarantees the system regular, impulse-free and stable for all admissible uncertainties, is obtained. Based on the strict linear matrix inequality, the desired robust state feedback controller is also obtained. Finally, a numerical example is provided to demonstrate the application of the proposed method.

Delay-dependent robust control for uncertain discrete singular systems with time-varying delay

The design problem of delay-dependent robust control for uncertain discrete singular systems with time-varying delay is addressed in this paper. The uncertainty is assumed to be norm-bounded. By establishing a finite sum inequality based on quadratic terms, a new delay-dependent robust stability condition is derived and expressed in terms of linear matrix inequalities (LMIs). A suitable robust state feedback control law is presented, which guarantees that the resultant closed-loop system is regular, causal and stable for all admissible uncertainties. Numerical examples are given to demonstrate the applicability of the proposed method.

MULTITARGET STATE AND TRACK ESTIMATION FOR THE PROBABILITY HYPOTHESES DENSITY FILTER

The particle Probability Hypotheses Density (particle-PHD) filter is a tractable approach for Random Finite Set (RFS) Bayes estimation, but the particle-PHD filter can not directly derive the target track. Most existing approaches combine the data association step to solve this problem. This paper proposes an algorithm which does not need the association step. Our basic ideal is based on the clustering algorithm of Finite Mixture Models (FMM). The intensity distribution is first derived by the particle-PHD filter, and then the clustering algorithm is applied to estimate the multitarget states and tracks jointly. The clustering process includes two steps: the prediction and update. The key to the proposed algorithm is to use the prediction as the initial points and the convergent points as the es- timates. Besides, Expectation-Maximization (EM) and Markov Chain Monte Carlo (MCMC) ap- proaches are used for the FMM parameter estimation.

A NEW METHOD FOR CONSTRUCTING FUZZY EVIDENCE BASED ON THE NON-CONSONANT RANDOM SET

Natural-language information is often mathematically expressed by fuzzy sets. With the random set theory as a bridge, this kind of information can be transformed into fuzzy evidence in Dempster-Shafer (DS) theory. Then Dempster's combination rule or other combination rules of evi- dence can be used perfectly for fusing natural-language and other information. However, this traditional transformation involves the use of α -cutsets to construct the focal elements which have to be repre- sented as consonant sets. This construction is very inflexible and unreasonable in some practical ap- plications. In this paper, with the desire to overcome this limitation, a method for constructing more general non-consonant focal elements is proposed based on the random set theory. Some examples are given to show the generality and the efficiency of this new method. Finally, we validate that non-consonant constructions provide less degrees of total uncertainty than that of the consonant case in these examples by using the evaluation criterion of total uncertainty.

解非线性动态优化问题的一种改进的控制矢量迭代方法.Ⅱ.带路径约束问题(英文)

This paper considers dealing with path constraints in the framework of the improved control vector iteration(CVI)approach.Two available ways for enforcing equality path constraints are presented,which can be directly incorporated into the improved CVI approach.Inequality path constraints are much more difficult to deal with,even for small scale problems,because the time intervals where the inequality path constraints are active are unknown in advance.To overcome the challenge,the l1penalty function and a novel smoothing technique are introduced,leading to a new effective approach.Moreover,on the basis of the relevant theorems,a numerical algorithm is proposed for nonlinear dynamic optimization problems with inequality path constraints.Results obtained from the classic batch reactor operation problem are in agreement with the literature reports,and the computational efficiency is also high.

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.

APPROXIMATE OPTIMAL BIRTH CONTROL OF POTULATION SYSTEMS

We consider optimal birth control for the McKendrick equation of population dyna-mics.It consists of optimizing a system described by a first order partial differential equationwith nonlo-cal bilinear boundary control.Approximate minimum principles are obtained usingEkeland’s vari ational principle.

非线性动态优化问题的改进控制矢量迭代法(Ⅰ)无路径约束问题(英文)

This study proposes an efficient indirect approach for general nonlinear dynamic optimization problems without path constraints. The approach incorporates the virtues both from indirect and direct methods: it solves the optimality conditions like the traditional indirect methods do, but uses a discretization technique inspired from direct methods. Compared with other indirect approaches, the proposed approach has two main advantages: (1) the discretized optimization problem only employs unconstrained nonlinear programming (NLP) algorithms such as BFGS (Broyden-Fletcher-Goldfarb-Shanno), rather than constrained NLP algorithms, therefore the computational efficiency is increased; (2) the relationship between the number of the discretized time intervals and the integration error of the four-step Adams predictor-corrector algorithm is established, thus the minimal number of time intervals that under desired integration tolerance can be estimated. The classic batch reactor problem is tested and compared in detail with literature reports, and the results reveal the effectiveness of the proposed approach. Dealing with path constraints requires extra techniques, and will be studied in the second paper.

A NOVEL METHOD FOR NETWORK WORM DETECTION BASED ON WAVELET PACKET ANALYSIS

Objective To detect unknown network worm at its early propagation stage. Methods On the basis of characteristics of network worm attack, the concept of failed connection flow (FCT) was defined. Based on wavelet packet analysis of FCT time series, this method computed the energy associated with each wavelet packet of FCT time series, transformed the FCT time series into a series of energy distribution vector on frequency domain, then a trained K-nearest neighbor (KNN) classifier was applied to identify the worm. Results The experiment showed that the method could identify network worm when the worm started to scan. Compared to theoretic value, the identification error ratio was 5.69%. Conclusion The method can detect unknown network worm at its early propagation stage effectively.

Enhanced H_∞ Filtering for Continuous-time State-delayed Systems

The H∞ filtering problem for continuous-time polytopic uncertain time-delay systems is investigated. Attention is focused on the design of full-order filters guaranteeing a prescribed H∞ attenuation level for the filtering error system. First, a simple alternative proof is given for an improved linear matrix inequality （LMI） representation of H∞ performance. Then, based on the performance criterion which keeps Lyapunov matrices out of the product of system dynamic matrices, a suficient condition for the existence of robust estimators is formulated in terms of LMIs, and the corresponding filter design is cast into a convex optimization problem which can be effciently handled by using standard numerical algorithms. It is shown that the proposed design strategy allows the use of parameter-dependent Lyapunov functions and hence it is less conservative than some earlier results. A numerical example is employed to demonstrate the feasibility and advantage of the proposed design.

A Distributed DBMS Based Dynamic Programming Method for Query Optimization

Dynamic programming(DP) is an effective query optimization approach to select an appropriate join order for relational database management system(RDBMS) in multi-table joins. This method was extended and made available in distributed DBMS(D-DBMS). The structure of this optimal solution was firstly characterized according to the distributing status of tables and data, and then the recurrence relations between a problem and its sub-problems were recursively defined. DP in D-DBMS has the same time-complexity with that in centralized DBMS, while it has the capability to solve a much more sophisticated optimal problem of multi-table join in D-DBMS. The effectiveness of this optimal strategy has been proved by experiments.

EXPONENTIAL STABILITY OF A REPARABLE MULTI-STATE DEVICE

一台多状态设备的指数的稳定性在这篇论文被讨论。我们在场 C 0-semigroup 由系统操作符产生了，这是伪协议；无法缩减。0 是系统操作员的一个简单特征值，这被知道。在有这的联合，我们获得时间依赖者答案指数地收敛到不变的答案，它是相应于简单特征值的积极 eigenfuction 0。

GLOBAL ASYMPTOTIC STABLE ERADICATION FOR THE SIV EPIDEMIC MODEL WITH IMPULSIVE VACCINATION AND INFECTION-AGE

我们学习脉搏种痘策略的申请根除在潜伏期有传染海角的慢慢地进行的疾病。我们导出根除答案是一个全球引起注意的人的在条件，这个条件取决于脉搏种痘比例 p。我们也获得答案的全球 asymptotic 稳定性的条件。Thecondition 显示出那个足够大的脉搏种痘比例并且相对小内部脉搏时间导致疾病的根除。而且理论学习的结果可能对 HIV 的传染病学有启发性。

GLOBAL STABILITY OF AN AGE-STRUCTURED SIR EPIDEMIC MODEL WITH PULSE VACCINATION STRATEGY

这份报纸讨论脉搏种痘策略的申请阻止并且控制传染疾病，它被组织年龄的先生描述在易受影响、恢复的个人到按年代先后的年龄在哪个被组织建模的一些，当感染的个人到感染年龄被组织时(持续时间自从感染) 。依赖没有疾病的平衡被决定的时间，为哪个明确的表情存在。分析结果证明那在那里存在一种全球性稳定的没有感染的状况如果冲动的时期 T 和比例 p 满足 R 0 (p， T )< 1。最佳的问题被讨论：有在给定的 R 0 的最小的费用的脉搏种痘策略(p， T )< 1。

FURTHER RESEARCH OF A NEW KIND OF SERIES REPAIRABLE SYSTEM

这篇论文被奉献给学习系统的唯一和存在由使用 C 0-semigroup 理论并且由分析讨论它的指数的稳定性的动态答案光谱系统操作员和它的伪紧密的分发。一些主要可靠性索引与系统操作员和最佳的假期时间的特徵函数被讨论得到最大的系统利润在纸的结束被分析。