Analytical redundancy and the design of robust failure detection systems

TLDR

The failure detection and identification process consists of residual generation and decision making, with analytical redundancy forming the basis of residual generation via parity space relations. The authors argue that robustness in FDI can be achieved by designing a robust residual generation process. Residuals can be generated through parity relations in multiple ways, and the design of a robust residual generation process is formulated as a minimax optimization problem, illustrated by an example.

Abstract

The failure detection and identification (FDI) process is viewed as consisting of two stages: residual generation and decision making. It is argued that a robust FDI system can be achieved by designing a robust residual generation process. Analytical redundancy, the basis for residual generation, is characterized in terms of a parity space. Using the concept of parity relations, residuals can be generated in a number of ways and the design of a robust residual generation process can be formulated as a minimax optimization problem. An example is included to illustrate this design methodology.