Fuzzy logic (FL) systems are widely established as a technology offering an alternative system to tackle compound and ill defined problems. They can be trained from examples, are fault tolerant in the sense that they are capable to grip noisy and deficient data, are able to deal with non-linear problems, and once trained can perform prediction and generalization at high speed. in this paper a simple fuzzy logic control has been developed which is used for defining engine system faults and control and maintain them in a normal range  without use any complicated mathematical equation and any fault sensor.

One of the new issues that marketers are facing is the effect of self-congruity on switching intention.The purpose of this study is to review the relationship among four dimensions of self-congruity (actual, ideal, social and ideal social congruity)

Abstract:The effect of self-congruity and functional congruity on switching intention is one new issue that marketers are encountering. The purpose of this study is to review the relationship among four dimensions of self-congruity (actual, ideal, social and ideal social congruity) and functional congruity with switching intention. To deepen the understanding of customers' switching decision formation, the researchers attempted to develop a switching intention model, consisted of self-image dimensions (actual, ideal, social, and ideal social self-congruity) and functional congruity. At the end of this paper, some new issues are recommended for the future research in this field.

A Multi Input Multi Output (MIMO) fuzzy estimator variable structure control (VSC) which containing an on-line controller coefficient tuned with the aim of a fuzzy back stepping algorithm. Satisfactory trajectories tracking among the internal combustion engine (IC engine) air to fuel ratio and the preferred input is certified in this paper. The fuzzy controller deployed in developed fuzzy estimator variable structure controller works using Lyapunov fuzzy inference system (FIS) with least model based rule base. Function among variable structure function, error and the error’s rate is represented by model. The outputs show fuel ratio. The fuzzy back stepping tactic is an on-line variable structure function fixing with the aim of an adaptive approach. MIMO fuzzy estimator and VSC performance with an on-line fuzzy back stepping algorithm (FBAFVSC) tuned with the aim of controller coefficient is confirmed using a comparison with VSC and planned approach. Simulation outputs indicate excellent presentation of fuel ratio in attendance of ambiguity and exterior annoyance.

This paper presents an online Artificial Fuzzy sliding Gain Scheduling Sliding Mode Control (AFSGSMC) design and its application to internal combustion (IC) engine high performance nonlinear controller in the presence of uncertainties and external disturbance. The fuzzy online tune sliding function in fuzzy sliding mode controller is based on Mamdanis fuzzy inference system (FIS) and it has multi input and multi output. The input represents the function between sliding function, error and the rate of error. The output represents the dynamic estimator to estimate the nonlinear dynamic equivalent in supervisory fuzzy sliding mode algorithm. The performance of the AFSGSMC was compared with the IC engine controller based on sliding mode control theory (SMC). Simulation results signify good performance of fuel ratio in presence of uncertainty and external disturbance