Reliability analysis of complex systems based on fault tree decomposition and Copula modeling

Traditional reliability modeling techniques based on the independence assumption tend to overstate system reliability, according to this study, which examines the strong coupling characteristics among several subsystems in complex control systems. To address this issue, a reliability analysis method combining fault tree decomposition and Copula modeling is proposed. Firstly, the complex control system is structurally decomposed using a fault tree to identify key failure modes and minimal cut sets. Secondly, the Copula function is employed to characterize the non-independent correlation among subsystems, and the expression for the overall system reliability is derived. Finally, a specific type of complex control system is taken as a case study, and the reliability results under the independence assumption and Copula modeling are compared. The study confirms that the traditional modeling approach based on the independence assumption has a significant overestimation risk by demonstrating that the reliability decline of this kind of complex control system during task execution is more significant after taking the coupling effect into account than that calculated by traditional methods. This method provides effective theoretical support for the reliability assessment and optimal design of complex control systems.