This research addresses system reliability analysis using weakest t-norm based approximate intuitionistic fuzzy arithmetic operations, where failure probabilities of all components are represented by different types of intuitionistic fuzzy numbers. Due to the incomplete, imprecise, vague and conflicting information about the component of system, the present study evaluates the reliability of sy...

This paper presents the basic concepts of stability in fuzzy linguistic models. Theauthors have proposed a criterion for BIBO stability analysis of fuzzy linguistic modelsassociated to linear time invariant systems [25]-[28]. This paper presents the basic concepts ofstability in the general nonlinear and linear systems. This stability analysis method is verifiedusing a benchmark system analysis.

One of most critical system in military vehicles is the suspension system and the reliability of the system is essential to maintain a mission capable status. When changes to the vehicle suspension system are warranted, the reliability of the system must be reevaluated to assure that service life is maintained. As the design to implementation cycles continue to be reduce, new tools are needed t...

this paper presents a fuzzy approach to the prediction of highly nonlinear timeseries.the optimized mamdani-type fuzzy system denoted sqp-flc is applied forthe input-output modeling of measured data. in order to tune fuzzy membershipfunctions, a sequential quadratic programming (sqp) method is employed. theproposed method is evaluated and validated on a highly complex time series, dailygold pri...

In this paper, ‎the multi-sensor fault diagnosis in the exhaust temperature sensors of a V94.2 heavy duty gas turbine is presented‎. ‎A Laguerre network-based fuzzy modeling approach is presented to predict the output temperature of the gas turbine for sensor fault diagnosis‎. Due to the nonlinear dynamics of the gas turbine, in these models the Laguerre filter parts are related to the linear d...

In some practical cases, it is not an easy to analyze the behavior of any complex repairable industrial system up to desired degree of accuracy due to vague, imprecise and uncertain data collected from the various resources (historical/present records). If somehow it can be done, then they have a high range of uncertainty. So, in order to reduce this uncertainty, to make a more sound decision f...

Abstract—Reliability allocation is quite important during early design and development stages for a system to apportion its specified reliability goal to subsystems. This paper improves the reliability fuzzy allocation method, and gives concrete processes on determining the factor and sub-factor sets, weight sets, judgment set, and multi-stage fuzzy evaluation. To determine the weight of factor...

Purpose: The aim of this study is applying a new method for Industrial robotic system selection. Design/methodology/approach: In this paper, the weights of each criterion are calculated using fuzzy Shannon’s Entropy. After that, fuzzy TOPSIS is utilized to rank the alternatives. After that we compare the result of Fuzzy TOPSIS with Fuzzy VIKOR method. Then we select the best Industrial Robotic ...

an asymptotically stable direct adaptive fuzzy pi sliding modecontroller is proposed for a class of nonlinear uncertain systems. in contrast toother existing approaches of handling disturbances, the proposed approachdoes not require this bound to be known, only requiring that it exists.moreover, a pi control structure is used to attenuate chattering. the approachis applied to stabilize an open-...

Exponentially stable trajectory following of robotic manipulators under a class of adaptive controls. In this paper we investigate the problem of fault diagnosis in rigid-link robotic manipulators. A learning architecture, with neural networks as on-line approximators of the oo-nominal system behavior, is used for monitoring the robotic system for faults. The approximation of the oo-nominal beh...