Robust Fault Diagnosis of Non-linear Systems using Constraints Satisfaction

Abstract: In this paper, the robust fault diagnosis problem for non-linear systems considering both bounded parametric modelling errors and noises is addressed using constraints satisfaction. Combining available measurements with the model of the monitored system, a set of analytical redundancy relations (ARR), relating only known variables, can be derived. These relations will be used in the fault diagnosis procedure to check the consistency between the observed and the predicted system behaviour. When some inconsistency is detected, the fault isolation mechanism will be activated in order to provide an explanation of the possible cause. Finally, a fault estimation procedure is used to estimate the fault size. To illustrate the usefulness of the proposed approach, a case study based on a well-known four tanks system benchmark is used. Copyright c © IFAC 200