A FUZZY MODEL FOR THE FAILURE OF COMPOSITE STRUCTURES

In this paper, the fuzzy theory is used to describe the uncertainty in failure definition of composite structures. The concept of structural failure level (SFL) is suggested and a method of evaluation is presented.

Fuzzy variable structure delay control algorithms and their applications to AQM

This paper analyzes the fuzzy variable structure control algorithms for delay systems and describes the compensation mechanism of the integral factor to the effect of the delay. Based on the linearized model of the congestion-avoidance flow-control mode of transmission control protocol (TCP), we present delay control algorithms for active queue management (AQM) and discuss the parameter tuning of the algorithms. The NS (network simulator) simulation results show that the proposed control scheme for the nonlinear TCP/AQM model has good performance and robustness with respect to the uncertainties of the round-trip time (RTT) and the number of active TCP sessions. Compared to other similar schemes, our algorithms perform better in terms of packet loss ratio, throughput and butter fluctuation.

Optimal design of structural parameters for shield cutterhead based on fuzzy mathematics and multi-objective genetic algorithm

In order to improve the strength and stiffness of shield cutterhead, the method of fuzzy mathematics theory in combination with the finite element analysis is adopted. An optimal design model of structural parameters for shield cutterhead is formulated,based on the complex engineering technical requirements. In the model, as the objective function of the model is a composite function of the strength and stiffness, the response surface method is applied to formulate the approximate function of objective function in order to reduce the solution scale of optimal problem. A multi-objective genetic algorithm is used to solve the cutterhead structure design problem and the change rule of the stress-strain with various structural parameters as well as their optimal values were researched under specific geological conditions. The results show that compared with original cutterhead structure scheme, the obtained optimal scheme of the cutterhead structure can greatly improve the strength and stiffness of the cutterhead, which can be seen from the reduction of its maximum equivalent stress by 21.2%, that of its maximum deformation by 0.75%, and that of its mass by 1.04%.

Genetic Algorithms of Structural Fuzzy Reliability Index

In this paper the simple generation algorithms are improved. According to the geometric meaning of the structural reliability index, a method is proposed to deal with the variables in the standard normal space. With consideration of variable distribution, the correlation coefficient of the variables and its fuzzy reliability index, the feasibility and the reliability of the algorithms are proved with an example of structural reliability analysis and optimization.

A kind of fuzzy control for chaotic systems

With a T-S fuzzy dynamic model approximating to a non-linear system,the nonlinear system can be decomposed into some local linear models.A variable structure controller based on Lyapunov theories is designed to guarantee the global stability of the T-S fuzzy model.The controlling problems of a nonlinear system can be solved by means of consisting of linear system variable structure control and fuzzy control.The validity of the control method based on the simulating result of two kinds of chaotic systems is shown here.

Fuzzy variable structure algorithms for active queue management with delay compensation

Based on the linearized model of the TCP connections through the congested routers, this paper puts forward an active queue management algorithm (FVS-T). The algorithm utilizes the fuzzy variable structure control algorithm with delay factor to compensate time varying round-trip times (RTT) and uncertainties with respect to the number of active TCP sessions. By analyzing the robustness and performance of the control scheme for the nonlinear TCP/AQM model, we show that the proposed design has good performance and robustness, which are central to the notion of AQM. Implementation issues were discussed and ns simulations were provided to validate the design and compare its performance to other peer schemes in different scenarios. The results show that the proposed design significantly outperforms the other congestion schemes in terms of packet loss ratio, throughput and buffer fluctuation.

Structural Reliability Analysis Method in Fuzzy Environment

In this paper, the fuzzy-set-based structural possibility theory is investigated, and this theory can be used to deal with the subjective uncertainties in the design of engineering structures. Furthermore, a comprehensive model of structural safety assessment, which can merge subjective uncertainties with objective uncertainties, is presented. In this model, the fuzziness of stress-strength inference model, safety margin functions of single or multiple limit-state, structural failure state and the final assessment result are taken into account. This continuous model can be transformed into an equivalent model of probability-based and solved by the present structural reliability analysis method and parallel algorithm. An example is given to show the main idea of the method presented in this paper.

Derivation and analysis on the analytical structure of interval type-2 fuzzy controller with two nonlinear fuzzy sets for each input variable

Type-2 fuzzy controllers have been mostly viewed as black-box function generators. Revealing the analytical structure of any type-2 fuzzy controller is important as it will deepen our understanding of how and why a type-2 fuzzy controller functions and lay a foundation for more rigorous system analysis and design. In this study, we derive and analyze the analytical structure of an interval type-2 fuzzy controller that uses the following identical elements: two nonlinear interval type-2 input fuzzy sets for each variable, four interval type-2 singleton output fuzzy sets, a Zadeh AND operator, and the Karnik-Mendel type reducer. Through dividing the input space of the interval type-2 fuzzy controller into 15 partitions, the input-output relationship for each local region is derived. Our derivation shows explicitly that the controller is approximately equivalent to a nonlinear proportional integral or proportional differential controller with variable gains. Furthermore, by comparing with the analytical structure of its type-1 counterpart, potential advantages of the interval type-2 fuzzy controller are analyzed. Finally, the reliability of the analysis results and the effectiveness of the interval type-2 fuzzy controller are verified by a simulation and an experiment.