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. Existing fuzzy voters for controlling safety critical systems and sensor fusion are surveyed and safety performance is empirically evaluated. The major limitation identified in the existing fuzzy voters is the static fuzzy parameter selection. Optimally selected static fuzzy parameters work only for a particular set of data with the known data ranges. In this paper, a dynamic or automatic fuzzy parameter selection method for fuzzy voters is proposed based on the statistical parameters of the local set of data 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 show that proposed Dynamic fuzzy voter is giving almost 100% safety if two of the three modules of the TMR System are error free. Dynamic voter is designed in such a way that it can be plugged in and used in any safety critical system without having any knowledge regarding the data produced and their ranges.