Robust Fault Diagnosis by Optimal Input Design for Self-sensing Systems
It addresses the need for reliable fault diagnosis in self-sensing systems, but the results are only demonstrated via simulation without quantitative benchmarks.
This paper develops a methodology for robust fault diagnosis and optimal input design for self-sensing systems, enabling real-time implementation with robustness to system uncertainty. The approach is validated through numerical simulations.
This paper presents a methodology for model based robust fault diagnosis and a methodology for input design to obtain optimal diagnosis of faults. The proposed algorithm is suitable for real time implementation. Issues of robustness are addressed for the input design and fault diagnosis methodologies. The proposed technique allows robust fault diagnosis under suitable conditions on the system uncertainty. The designed input and fault diagnosis techniques are illustrated by numerical simulation.