Parallel distributed compensator design of tank level control based on fuzzy Takagi–Sugeno model

In this paper, a fuzzy controller is designed based on parallel distributed compensation (PDC) method and it is implemented in an experimental tank level control system. Firstly, a mathematical model of the system is obtained experimentally. An important feature of the plant is its nonlinearity. To control the level of water in the tank over the whole range, the nonlinear model of the system is linearized around three different operating points. Then, three PI controllers are designed for the operating points, using Skogestad's method. By using the PDC method, an overall fuzzy controller is designed by the fuzzy blending of the three PI-controllers. To evaluate the practical performance of the PDC-based fuzzy controller, the control system is implemented in the experimental system. The evaluation criteria considered are step response and disturbance rejection. The comparison results showed the superiority of the PDC-controller over the classical PI-controller.     

通用基础软件等级保护测评原型的研究

随着我国软件事业的迅速发展，软件安全问题也逐渐增多，给人们的正常生活、生产和工作带来了不同程度的危害和损失。当前软件安全问题已经成为了社会和人们关注的焦点问题，要提高软件的安全级别，还需要建立一套科学、系统的软件安全评估标准。虽然当前在基础软件服务上已经出台了一套行业标准，但是这些标准的统一性和可操作性还不够高，仍然存在很多不足之处，因此还需要探索新的安全测试标准体系，以用于指导国产通用基础软件的安全测试工作。     

COMPARATIVE STUDY OF FUZZY CONTROL,PID CONTROL,AND ADVANCED FUZZY CONTROL FOR SIMULATING A NUCLEAR REACTOR OPERATION

Based on the background of fuzzy control applications to the first nuclear reactor in Belgium (BR1) at the Belgian Nuclear Research Centre (SCK˙CEN), we have made a real fuzzy logic control demo model. The demo model is suitable for us to test and compare some new algorithms of fuzzy control and intelligent systems, which is advantageous because it is always difficult and time-consuming, due to safety aspects, to do all experiments in a real nuclear environment. In this paper, we first report briefly on the construction of the demo model, and then introduce the results of a fuzzy control, a proportional-integral-derivative (PID) control and an advanced fuzzy control, in which the advanced fuzzy control is a fuzzy control with an adaptive function that can self-regulate the fuzzy control rules. Afterwards, we present a comparative study of those three methods. The results have shown that fuzzy control has more advantages in terms of flexibility, robustness, and easily updated facilities with respect to the PID control of the demo model, but that PID control has much higher regulation resolution due to its integration term. The adaptive fuzzy control can dynamically adjust the rule base, therefore it is more robust and suitable to those very uncertain occasions.     

Defuzzification as a special way of dealing with retranslation

The problem of defuzzification is examined in this paper from a broader perspective as a special way of dealing with the general problem of retranslation. The paper includes an overview of different formulations of the problem of defuzzification, as well as an overview of methods that have been suggested in the literature for dealing with the problem. Our own approach to defuzzification, which is described in the paper in more details, is based on relevant measures of uncertainty-based information. This paper is a companion to our recent paper that addresses the general problem of retranslation in computing with perceptions (Martin and Klir 2006).     

A multi-item transportation problem with fuzzy tolerance

This paper presents the recently introduced modified subgradient method for optimization and its effectiveness in a fuzzy transportation model. Here a multi-item balanced transportation problem (MIBTP) is formulated where unit transportation costs are imprecise. Also available spaces and budgets at destinations are limited but imprecise. The objective is to find a shipment schedule for the items that minimizes the total cost subjected to imprecise warehouse and budget constraints at destinations. The proposed model is reduced to a multi-objective optimization problem using tolerances, then to a crisp single-objective one using fuzzy non-linear programming (FNLP) technique and Zimmermann's method. The above fuzzy MIBTP is also reduced to another form of deterministic one using modified sub-gradient method (MSM). These two crisp optimization problems are solved by Genetic Algorithm (GA). As an extension, fuzzy multi-item balanced solid transportation problems (STPs) with and without restrictions on some routes and items are formulated and reduced to deterministic ones following FNLP and Zimmermann's methods. These models are also solved by GA. Models are illustrated numerically, optimum results of fuzzy MIBTP from two deductions are compared. Results are also presented for different GA parameters.     

Fracture behaviour of 8%Ni 980 MPa high strength steel at various temperatures Part 3 – Four-point notched bend tests

Abstract

Based on the results of four-point notched bend tests together with detailed microscopic observations of fracture surfaces and crack configurations below the unbroken notch roots of double notch specimens, the fracture mechanisms in notched specimens of 8%Ni high strength (980 MPa) steel have been observed to be as follows. A fibrous crack initiates in the bainitic matrix at the notch root and then develops into a cleavage crack at a critical length. The cleavage crack propagates in an unstable manner and causes the final fracture of specimen. The critical event controlling the cleavage fracture is the propagation of the bainitic packet-sized crack, and the local fracture stress is measured as around 1845–2200 MPa.     

ORDERING FUZZY SETS BY CONSENSUS CONCEPT AND FUZZY RELATION EQUATIONS

A general class of consensus measures of fuzzy sets is introduced in this paper. It is shown that, while the consensus measures are valuations but neither isotone nor antitone with respect to the lattice structure induced by the pointwise maximum and minimum operations to the set of all the fuzzy sets on a nonempty crisp set, they are antitone valuations with respect to the lattice structure induced by the generalized sharpening relation to a quotient set of the set of fuzzy sets. It is also shown that the solutions of a finite fuzzy relation equation that have the maximum consensus measure can be characterized through the join operation of the latter lattice in terms of the maximum solution and some of the minimal solutions of the equation.     

An application of OWA operators in fuzzy business diagnosis

The paper aims to develop an adjustment index based on OWA operators to enrich the results of diagnostic fuzzy models of business failure. A proposal to verify the diseases prediction accuracy of the models is also added. This allows a reduction of the map of causes or diseases detected in strategic defined areas. At the same time, these key areas can be disaggregated when an alert indicator is identified, and shows which of the causes need special attention. This application of OWA can encourage the development of suitable computer systems for monitoring companies’ problems, warn of failures and facilitate decision-making. In addition, taking Vigier and Terceño’s 2008 model as a benchmark, causes aggregation operators are introduced to evaluate alternative groupings, and the adjustment measure using approximate solutions is proposed to test the model’s prediction.The empirical estimation and the verification of the improvement proposals in a set of small and medium- sized enterprises (SMEs) in the construction industry are also presented. The functionality and the prediction capacity are thus measured and detected by monitoring key areas that warn about insolvency situations in the firm.     

Classification: Methods for the Exploratory Analythi of Multivariate Data

A fuzzy clustering strategy is used to identify subsets of influential observations in regression. As part of the fuzzy clustering strategy, the analyst can explore the uniqueness of selected subsets and the degree of belonging of observations to selected subsets. This is accomplished by either varying a fuzzy parameter or the number of clusters. Once the observations or subsets have been identified, the analyst can then compute regression diagnostics to confirm their degree of influence in regression. Bootstrapping and high-breakdown procedures were used to confirm the influence of the previously identified subsets. This fuzzy clustering strategy is applied to the modified data on wood-specific gravity and an augmented production dataset. Both datasets have been previously presented in the literature.     

Effect of Nb on Mechanical Properties of HAZ for High-Nb X80 Pipeline Steels

The mechanical properties of heat affected zone (HAZ) of two commercial high-Nb X80 grade pipeline steels with different alloy elements were investigated using thermal simulation performed on a Gleeble-3500 thermal simulator. The results showed that the high-Nb steels have excellent weldability. Embrittlement regions appear in coarse grain heat affected zone (CGHAZ) and intercritically heat affected zone (ICHAZ); Softening region appears in fine-grain heat affected zone (FGHAZ), and the strength here was even lower than 555 MPa as required in the standard. Meanwhile, with the increase of heat input, the strength and the toughness of HAZ of steel with high Nb, C and lower alloy decrease notably. Therefore, take into account the welding procedure during manufacture of weld pipe, suitable amount of alloy elements, such as Cr, Ni, Cu, Mo and so on, is necessary for high Nb X80 heavy-thick steel plate.