AN IMPROVEMENT IN HISTORY BASED WEIGHTED VOTINGALGORITHM FOR SAFETY CRITICAL SYSTEMS

Abstract

Fault masking is a widely used strategy for increasing the safety and reliability of computer control systems. Voting algorithms are used to arbitrate between the results of redundant modules in fault-tolerant systems. Inexact majority and weighted average voters have been used in many applications, although both have problems associated with them. Inexact majority voters require an application-speci6c ’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. The approach uses some form of voting to arbitrate between the results of hardware or software redundant modules for masking faults. Several voting algorithms have been used in fault tolerant control systems; each has different features, which makes it more applicable to some system types than others. Fault masking is one of the primary approaches to improve or maintain the normal behavior of a range of safety-critical systems. Some industrial sectors which employ such systems include process control, Transportation, nuclear power station and military applications Majority and weighted average voters have been widely used in these applications to provide error/fault-masking capability. Safety critical systems are the systems which may lead to hazards, loss of lives and great damage to the property if they fail due to errors which may lead to faults. N-Modular Redundancy or N-Version Programming along with the voter is used in the safety critical systems to mask the faults. This paper introduces a novel voting scheme based on fuzzy set theory. The voter assigns a fuzzy difference value to each pair of voter inputs based on their numerical distance. A set off fuzzy rules then determines a single fuzzy agreeability value for each individual input which describes how well it matches the other inputs. The agreeability of each voter input is then defuzzi6ed to give a weighting value for that input which determines its contribution to the voter output. The weight values are then used in the weighted average algorithm for calculating the voter 6nal output. 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. The impact of changing some fuzzy variables on the performance of the voter is also investigated. We show that the fuzzy voter gives more correct outputs (higher availability) than the inexact majority voter with small and large errors, less incorrect outputs (higher safety) than the inexact majority voter in the presence of small errors, and less benign outputs than the inexact majority voter. In this paper different existing weighted average voting algorithms are surveyed and their merits and demerits or limitations are discussed based upon which a novel History based weighted Voting algorithm with Soft Dynamic threshold is proposed. Experimentation results of the novel voting algorithm for Triple Modular Redundant (TMR) system are compared with existing voting algorithms and the novel voter is giving almost 100% Safety if two of the three modules are error free and giving better results for one error free module. Novel voter is also giving better results for the multiple error conditions with all the modules having errors.