Self Configurable Dynamic Fuzzy Voter for Safety Critical Systems using Statistical Parameters

Vol.6 No.1

Year: 2011

Issue: July-September

Title: Self Configurable Dynamic Fuzzy Voter for Safety Critical Systems using Statistical Parameters   

Author Name: Phani Kumar, SeethaRamaiah Panchumarthy                                   

Synopsis: 

The main objective of this research paper is designing automatic fuzzy parameter selection based dynamic fuzzy voter for safety critical systems with limited system knowledge. In this research paper, existing fuzzy voters for controlling safety critical systems and fuzzy voters used for sensor fusion are surveyed and the major limitation identified in the existing fuzzy voters, is the static fuzzy parameter selection. Static fuzzy parameters work only for a particular set of data with the known data ranges for which optimized values are selected for fuzzy parameters. These values may not work for other sets of data with different ranges. The static fuzzy parameter selection method may not work for continuously changing different ranges of data. In this paper a dynamic or automatic fuzzy parameter selection method for fuzzy voters is proposed based upon the local set of data in each voting cycle. Fuzzy bandwidth is decided based upon the statistical parameters like mean of the local data set and standard deviation and fuzzy parameters are updated to decide the fuzzy bandwidth in each voting cycle. Safety performance is empirically evaluated by running the static and dynamic fuzzy voters on a simulated Triple Modular Redundant (TMR) system for 10000 voting cycles. Experimental results shows that proposed Dynamic fuzzy voter is giving almost 100% safety if two of the three modules of the TMR System are error free and also giving better safety performance compared to the existing static fuzzy voter for multiple error conditions. Dynamic voter is designed in such a way that it can be just plugged in and used in any safety critical system without having any knowledge regarding the data produced and their ranges, as it processes the data locally in each voting cycle using statistical parameters.