Stable Fault-tolerance Control for a Class of Networked Control Systems

In this paper, we use the matrix measure technique to study stable fault-tolerance control of networked control systems. State feedback networked control systems with the network-induced delay, parameter uncertainties, sensor failures and actuator failures are considered. State feedback gain K is designed for any invariant delay τ, and some theorems and sufficient conditions for stable fault-tolerance control are given. Example is presented to illustrate the effectiveness of these theorems.

A New Approach to Robust Stability Analysis of Sampled-data Control Systems

The lifting technique is now the most popular tool for dealing with sampled-data controlsystems. However, for the robust stability problem the system norm is not preserved by the liftingas expected. And the result is generally conservative under the small gain condition. The reason forthe norm di?erence by the lifting is that the state transition operator in the lifted system is zero inthis case. A new approach to the robust stability analysis is proposed. It is to use an equivalentdiscrete-time uncertainty to replace the continuous-time uncertainty. Then the general discretizedmethod can be used for the robust stability problem, and it is not conservative. Examples are givenin the paper.

UKF-based attitude determination method for gyroless satellite

UKF (unscented Kalman filtering) is a new filtering method suitable to nonlinear systems. The method need not linearize nonlinear systems at the prediction stage of filtering, which is indispensable in EKF ( extended Kalman filtering) . As a result, the linearization error is avoided, and the filtering accuracy is greatly improved. UKF is applied to the attitude determination for gyroless satellite. Simulations are made to compare the new filter with the traditional EKF. The results indicate that under same conditions, compared with EKF, UKF has faster convergence speed, higher filtering accuracy and more stable estimation performance.

Delay-Dependent Absolute Stability ofUncertain Lur′e Systems with Time-Delays^1）

This paper is concerned with delay dependent absolute stability for a class of uncertain Lur′e systems with multiple time-delays. By using a descriptor model transformation of the sys-tem and by applying a recent result on bounding of cross products of vectors, a new type of Lya-punov-Krasovskii functional is constructed. Based on the new functional, delay-dependent suffi-cient conditions for absolute stability are derived in terms of linear matrix inequalities. These con-ditions do not require any parameter tuning, and can be solved numerically using the software LMI Lab. A numerical example is presented which shows that the proposed method can substantiallyimprove the delay bound for absolute stability of Lur′e system with time-delays, compared to theexisting ones.

On the order of stable compensators for a class of time-delay system

The stabilization using a stable compensator does not introduce additional unstable zeros into the closed-loop transfer function beyond those of the original plant, so it is a desirable compensator, the price is that the compensator’s order will go up. This note considered the order of stable compensators for a class of time-delay systems. First, it is shown that for single-loop plants with at most one real right-half plane zero, a special upper bound for the minimal order of a strongly stabilizing compensator can be obtained in terms of the plant order; Second, it is shown that approximate unstable pole-zero cancellation does not occur, and the distances between distinct unstable zeroes are bounded below by a positive constant, then it is possible to find an upper bound for the minimal order of a strongly stabilizing compensator.

Delay-dependent guaranteed cost control for uncertain systems with both state and input delays

This paper considers the guaranteed cost control problem for a class of uncertain linear systems with both state and input delays. By representing the time-delay system in the descriptor system form and using a recent result on bounding of cross products of vectors, we obtain new delay-dependent sufficient conditions for the existence of the guaranteed cost controller in terms of linear matrix inequalities. Two examples are presented which show the effectiveness of our approach.

Decision making with fuzzy probability assessments and fuzzy payoff

A novel method for decision making with fuzzy probability assessments and fuzzy payoff is presented. The consistency of the fuzzy probability assessment is considered. A fuzzy aggregate algorithm is used to indicate the fuzzy expected payoff of alternatives. The level sets of each fuzzy expected payoff are then obtained by solving linear programming models. Based on a defuzzification function associated with the level sets of fuzzy number and a numerical integration formula (Newton-Cotes formula), an effective approach to rank the fuzzy expected payoff of alternatives is also developed to determine the best alternative. Finally, a numerical example is provided to illustrate the proposed method.

Off-Line Identification of Induction Motor Parameters

This study presented an off-line identification method of induction motor (IM) parameters. Before startup,the inverter drive performed automatically a modified DC test, a locked-rotor test, a no-load test and a step-voltage test to identify all the parameters of an induction motor. No manual operation and speed signals were required in the process. In order to obtain effective messages and improve the accuracy of identification, the discrete fast Fourier transform (DFFT) and the least-squares were used to process the signals of currents and voltages. A phase-voltage measuring method for motors was also proposed, which measured directly the actual conducting time of three upper switches in the inverter without need for a dead-time compensator. The validity, reliability and accuracy of the presented methods have been verified by the experiments on a VSI-fed IM drive system.

Adaptive tracking controller using BP neural networks for a class of nonlinear systems

An BP neural-network-based adaptive control (NNAC) design method is described whose aim is to control a class of partially unknown nonlinear systems. Making use of the online identification of BP neural networks, the results of the identification could be used into the parameters of the controller. Not only the strong robustness with respect to uncertain dynamics and nonlinearities can be obtained, but also the output tracking error between the plant output and the desired reference output can asymptotically converge to zero by Lyapunov theory in the process of this design method. And a simulation example is also presented to evaluate the effectiveness of the design.

Color Image Enhancement Based on Maximum Fuzzy Entropy

A color image enhancement approach based on maximum fuzzy entropy and genetic algorithm is proposed in this paper. It enhances color images by stretching the contrast of S and I components respectively in the HSI color representation. The image is transformed from the property domain to the fuzzy domain with S-function. To preserve as much information as possible in the fuzzy the domain, the fuzzy entropy function is used as objective function in a genetic algorithm to optimize three parameters of the S-function. The Sigmoid function is applied to intensify the membership values and the results are transformed back to the property domain to produce the enhanced image. Experiments show the effectiveness of the approach.

Robust L_1 filtering with pole constraint in a disk via parameter-dependent Lyapunov functions

The problem of robust L 1 filtering with pole constraint in a disk for linear continuous polytopic uncertain systems is discussed. The attention is focused on design a linear asymptotically stable filter such that the filtering error system remains robustly stable, and has a L 1 performance constraint and pole constraint in a disk. The new robust L 1 performance criteria and regional pole placement condition are obtained via parameter-dependent Lyapunov functions method. Upon the proposed multiobjective performance criteria and by means of LMI technique, both full-order and reduced-order robust L 1 filter with suitable dynamic behavior can be obtained from the solution of convex optimization problems. Compared with earlier result in the quadratic framework, this approach turns out to be less conservative. The efficiency of the proposed technique is demonstrated by a numerical example.

Solving function optimization problems with the immune principle

Adaptive immune evolutionary algorithm is proposed based on the principle of adaptive immune response. Two new algorithm parameters of expansion radius and mutation radius are defined to construct a small neighborhood and a large neighborhood, then expansion and mutation operations are designed to search the local and global regions of solution space simultaneously by using the two neighborhoods, thus, two-level neighborhood search mechanism is realized. The degree of the diversity in the population is described with the average Euclidean distance among all individuals, and it is used to adjust algorithm parameters adaptively to accelerate convergence and avoid getting stuck at local optima. The algorithm is proved to be convergent and its optimization principle is analyzed. The experiment results of multi-modal function optimization show that the algorithm is effective.

A novel clustering and supervising users' profiles method

To better understand different users' accessing intentions, a novel clustering and supervising method based on accessing path is presented. This method divides users' interest space to express the distribution of users' interests, and directly to instruct the constructing process of web pages indexing for advanced performance.

New Hybrid Genetic Algorithm for Vertex Cover Problems

This paper presents a new hybrid genetic algorithm for the vertex cover problems in which scan-repair and local improvement techniques are used for local optimization. With the hybrid approach, genetic algorithms are used to perform global exploration in a population, while neighborhood search methods are used to perform local exploitation around the chromosomes. The experimental results indicate that hybrid genetic algorithms can obtain solutions of excellent quality to the problem instances with different sizes. The pure genetic algorithms are outperformed by the neighborhood search heuristics procedures combined with genetic algorithms.

Splicing-site recognition of rice (Oryza sativa L.)DNA sequences

Motivation: It was found that high accuracy splicing-site recognitio n of rice (Oryza sativa L.) DNA sequence is especially difficult. We describe d a new method for the splicing-site recognition of rice DNA sequences. Method: Bas e d on the intron in eukaryotic organisms conforming to the principle of GT-AG,w e used support vector machines (SVM) to predict the splicing sites. By machine l earning,we built a model and used it to test the effect of the test data set of true and pseudo splicing sites. Results: The prediction accuracy we obtained wa s 87.53% at the true 5' end splicing site and 87.37% at the true 3' end splicing sites. The results suggested that the SVM approach could achieve higher accuracy than the previous approaches.

A Sufficient Condition of Hamilton Connected Graph

Let G be a 3-connected graph with n vertices. The paper proves that if for each pair of vertices u and v of G, d(u,v)=2, has ｜N(u)∩N(v)｜≤α(α is the minimum independent set number), and then max{d(u),d(v)}≥n+12, then G is a Hamilton connected graph.

Sticker DNA computer model ——Part Ⅰ: Theory

Sticker model is one of the basic models in the DNA computer models.This model is coded with sin-gle-double stranded DNA molecules.It has the following ad-vantages that the operations require no strands extension and use no enzymes; Whats more, the materials are reusable. Therefore it arouses attention and interest of scientists in many fields. In this paper, we will systematically analyze the theories and applications of the model,summarize other sci-entists contributions in this field,and propose our research results.This paper is the theoretical portion of the sticker model on DNA computer, which includes the introduction of the basic model of sticker computing. Firstly, we systemati-cally introduce the basic theories of classic models about sticker computing; Secondly, we discuss the sticker system which is an abstract computing model based on the sticker model and formal languages; Finally, extend and perfect the model,and present two types of models that are more exten-sive in the applications and more perfect in the theory than the past models: one is the so-called k-bit sticker model,the other is full-message sticker DNA computing model.

A fast learning algorithm of neural network with tunable activation function

This paper presents a modified structure of a neural network with tunable activation function and provides a new learning algorithm for the neural network training. Simulation results of XOR problem, Feigenbaum function, and Henon map show that the new algorithm has better performance than BP (back propagation) algorithm in terms of shorter convergence time and higher convergence accuracy. Further modifications of the structure of the neural network with the faster learning algorithm demonstrate simpler structure with even faster convergence speed and better convergence accuracy.

EXISTENCE AND UNIQUENESS OF PERIODIC SOLUTION OF DELAYED LOGISTIC EQUATION AND ITS ASYMPTOTIC BEHAVIOR

In this paper, our main aim is to study the existence and uniqueness of the periodic solution of delayed Logistic equation and its asymptotic behavior. In case the coefficients are periodic, we give some sufficient conditions for the existence and uniqueness of periodic solution. Furthermore, we also study the effect of time-delay on the solution.

CLOSURE AXIOMS FOR POSET MATROIDS

An excellent introduction to the topic of poset matroids is due to M, Barnabei, G, Nicoletti and L. Pezzoli. In this paper, we extensively study the closure operators of poset matroids and obtain the closure axioms for poset matroids; thereby we can characterize poset matroids in terms of the closure axioms. Some corresponding properties of combinatorial schemes are also obtained.