Robust fault isolation for a class of non-linear input-output systems

The design and analysis of fault diagnosis methodologies for non-linear sys tems has received significant attention recently. This paper presents a rob ust fault isolation scheme for a class of non-linear systems with unstructu red modelling uncertainty and partial state measurement. The proposed fault diagnosis architecture consists of a fault detection and approximation est imator and a bank of isolation estimators. Each isolation estimator corresp onds to a particular type of fault in the fault class. A fault isolation de cision scheme is presented with guaranteed performance. If at least one com ponent of the output estimation error of a particular fault isolation estim ator exceeds the corresponding adaptive threshold at some finite time, then the occurrence of that type of fault can be excluded. Fault isolation is a chieved if this is valid for all but one isolation estimator. Based on the class of non-linear systems under consideration, fault isolability conditio ns are rigorously investigated, characterizing the class of non-linear faul ts that are isolable by the proposed scheme. Moreover, the non-conservative ness of the fault isolability conditions is illustrated by deriving a subcl ass of nonlinear systems and faults for which this condition is also necess ary for fault isolability. A simulation example of a simple robotic system is used to show the effectiveness of the robust fault isolation methodology .