In this note, fault detection techniques based on finite dimensionalresults are extended and applied to a class of infinite dimensionaldynamical systems. This special class of systems assumes linearplant dynamics having an abrupt additive perturbation as the fault.This fault is assumed to be linear in the (unknown) constant (and possiblyfunctional) parameters.An observer-based model estimate is proposed which servesto monitor the system's dynamics for unanticipated failures,and its well posedness is summarized.Using a Lyapunov synthesis approach extended and applied to infinitedimensional systems, a stable adaptive fault diagnosis(fault parameter learning) scheme is developed. The resulting parameteradaptation rule is able to “sense” the instance of the fault occurrence.In addition, it identifies the fault parameters using the additionalassumption of persistence of excitation. Extension of the adaptivemonitoring scheme to incipient faults (time varying faults) is summarized.Simulations studies are used to illustrate the applicabilityof the theoretical results.
