A TMR Genetic Voting Algorithm for Fault-tolerant Medical Robot

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. It's important for a variety of reasons that safety critical systems execute without errors, and we always expect the system must work under any situation. There are different domains in which systems are used that we focused on the biomedical robots and fly by wire systems. A biomedical system is one which interfaces with humans in a medical context. Fly-by-wire (FBW) is a system that replaces the conventional manual flight controls of an aircraft with an electronic interface. This paper presents a layered fault tolerance framework for safety critical systems. Triple Modular Redundancy (TMR) method with weighted average voter and Genetic Algorithm (GA) is used in the sensor section. A voter circuit of the TMR will choose one of three sensor output to be processed further. Application of TMR will tolerate faults in the sensor section. The performance of voting algorithm is computed through a series of fault injection experiments and the results are compared with weighted average voting algorithms. The obtained results of simulating using MATLAB showed that the suggested algorithm gives better safety in comparison to the studied voting algorithms. Therefore, it's the best option for using in the fault tolerance of medical robots and fly-by-wire systems.