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In this note, fault detection techniques based on finite dimensional results are extended and applied to a class of infinite dimensional dynamical systems. This special class of systems assumes linear plant dynamics having an abrupt additive perturbation as the fault. This fault is assumed to be linear in the (unknown) constant (and possibly functional) parameters. An observer-based model estimate is proposed which serves to monitor the system’s dynamics for unanticipated failures, and its well...
In this note, fault detection techniques based on finite dimensional
results are extended and applied to a class of infinite dimensional
dynamical systems. This special class of systems assumes linear
plant dynamics having an abrupt additive perturbation as the fault.
This fault is assumed to be linear in the (unknown) constant (and possibly
functional) parameters.
An observer-based model estimate is proposed which serves
to monitor the system's dynamics for unanticipated failures,
and its well...
In this note, we employ nonlinear on-line parameter estimation methods based on adaptive neural network approximators for detecting changes due to actuator faults in a class of second order distributed parameter systems. The motivating example is a cantilevered beam actuated via a pair of piezoceramic patches. We examine changes in the control input term, which provide a simple and practical model of actuator failures. Using Lyapunov redesign methods, a stable learning scheme for fault diagnosis...
The purpose of this note is to investigate the existence of solutions to a class of second order distributed parameter systems with sudden changes in the input term. The class of distributed parameter systems under study is often encountered in flexible structures and structure-fluid interaction systems that use smart actuators. A failure in the actuator is modeled as either an abrupt or an incipient change of the actuator map whose magnitude is a function of the measurable output. A Galerkin-based...
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