Several voting algorithms have been described to arbitrate the results of redundant modules in fault-tolerant systems. The inexact majority and weighted average voters are widely used in control and safety-critical applications. Inexact majority voters require an application-specific ‟voter threshold‟ value to be specified, whereas weighted average voters are unable to produce a benign output when no agreement exists between the voter inputs. A major difficulty with inexact majority voters is the need to choose an appropriate threshold value, which has a direct impact on the voter performance. The problem of all documented weighted average voters is their inability to produce a benign output in cases of complete disagreement between the voter inputs. Both types of voters are unable to cope with uncertainties associated with voter inputs originated from erroneous software, noisy environment, or noisy hardware modules. A voting scheme based on fuzzy set theory was introduced which softens the harsh behaviour of the inexact majority voter in the neighbourhood of the „voter threshold‟ and handles uncertainty and some multiple error cases in the region defined by the fuzzy input variables. A set of fuzzy rules determines a single fuzzy agreeability value for each individual input which describes how well it matches the other inputs. The voter is experimentally evaluated from the point of view safety and availability and compared with the inexact majority voter in a Triple Modular Redundant structured framework. It is predicted that the fuzzy voter can be invaluable in at least two cases 1) as a substitute for the inexact majority voter in applications in which a small degradation in the safety performance of the system is acceptable at the cost of a large increase of its availability and a considerable decrease of its benign outputs 2) when arbitrating between the responses of dynamic channels of control systems which may include some uncertainty. 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. 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.