Quadruple adaptive redundancy with fault detection estimator

As a result of advances in technology, systems have grown more and more complex, leading to greater opportunities for failure. System fault has become an increasingly significant threat to the reliability and fault tolerance of automation systems. Redundancy of components within the system is one popular method for enhancing fault tolerance. One of the simple and effective methods for fault tolerance that has stood the test of time is Triple Modular Redundancy, which provides not one redundant copy of a critical system component, but two extra copies for a total of three. Ironically, providing three copies of a sensor, for example, only provides tolerance to one failure. It takes four copies to provide resilience to a double-point failure, but this can be expensive in terms of the cost of sensors and installation, wiring, and interface circuitry. We propose Quadruple Adaptive Redundancy, a new method that adds software-based estimation techniques, rather than additional hardware components, to achieve higher levels of robustness with virtually no incremental cost. In this paper, the performance of Quadruple Adaptive Redundancy is verified through computer simulations and compared to Triple Modular Redundancy with one and two induced sensor failures.