Voting Algorithm Based on Adaptive Neuro FuzzyInference System for Fault Tolerant Systems

Some applications are critical and must design Fault Tolerant System. UsuallyVoting Algorithm is one of the principle elements of a Fault Tolerant System. Twokinds of voting algorithm are used in most applications, they are majority votingalgorithm andMajority confronts with the problem of threshold limits and voter of weightedaverage are not able to produce safe outputs when obtaining a correct output isimpossible and also both of them aerror limit. In the present paper, delivering a voter for safety system, AdaptiveNeurotrained through Hybrid learning algorithm that isinference system, subtractive clustering and fuzzy Cthat delivered voter produced more safety outputs especially for small erroramplitude.-Fuzzy Inference System (ANFIS) is proposed. The above mentioned model isweighted average algorithm these algorithms have some problems.re not able to perform appropriately in smalleffective and using basic Fuzzy-means method. Results show

Keywords:

ANFIS , Adaptive NeuroSystems , Safety-Critical Systems-Fuzzy Inference System , Voting Algorithm , Fault Tolerant