Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7108832 | Automatica | 2018 | 7 Pages |
Abstract
Many recently developed data-driven fault estimation methods are restricted to minimum-phase systems so that their practical applications are limited. In this paper, the data-driven fault estimation for non-minimum phase (NMP) systems is studied, for which the main difficulty is that the unstable zeros of an NMP system will result in a growing fault-estimation error. To deal with this problem, the inverse of an NMP system is equivalently formulated as a mixed causal and anti-causal system, and the proposed fault estimator is the sum of a stable causal filter and a stable anti-causal filter. The proposed fault estimator is shown to be asymptotically unbiased and its performance is demonstrated by numerical simulations.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Chengpu Yu, Michel Verhaegen,