Markov reliability models for digital flight control systems

The reliability of digital flight control systems can often be accurately predicted! using Markov chain models. We begin our discussion of flight control system reliability models with definitions of key terms. We then construct a single-fault one-processor model based on the results of fault-injection experiments. To illustrate more complex system models, we consider several models of a triple modular redundant system. Once we have constructed some representative Markov reliability models, we discuss numerical techniques for their solution. The cost of numerical solution depends on a model's size and stiffness. Acyclic Markov models, a useful special case, are particularly amenable to efficient numerical solution. Even in the general case, instantaneous coverage approximation allows the reduction of some cyclic models to more readily solvable acyclic models. After considering the solution of single-phase models, we extend our discussion to phased-mission models. We classify phased-mission reliability models based on the state restoration behavior that occurs between mission phases: As an economical approach for the solution of such models, we introduce the mean failure rate solution method. We use a numerical example to show the influence of fault-model parameters and interphase behavior on system unreliability. © 1989 American Institute of Aeronautics and Astronautics, Inc. All rights reserved.