Fault Detection and Diagnosis enhanced by a reconfiguration control scheme for a micro-electrostatic actuator

Abstract

In this article, a Fault Detection and Diagnosis (FDD) strategy based on Set Membership Identification is proposed for the supervision of an electrostatic microactuator subject to failure modes in its structural components. Relying on the a priori knowledge of the bound of the noise corrupting the measurement data, the parametric uncertainty is assumed to be bounded and the SMI computes the parametric sets (ellipsoids, support-orthotopes), within which the nominal parameter vector resides. A fault is detected at the time instant that an empty parametric set is obtained. Prior to the fault isolation and identification procedure, a control reconfiguration scheme is used for prevention of catastrophic damages in the system, due to large parameter variations. Simulations studies are used to verify the efficiency of the suggested strategy.

Fault Detection and Diagnosis relying on Set Membership Identification for time varying systems

“…The data-hyperspace is configured as the hyperspace either between two parallel hypeplanes, called hereafter datahyperstrip [2], or between two non-parallel hyperplanes, called hereafter data-hypersector. a) Data-hyperstrip: The data-hyperstrip S p (i) is defined as:…”

“…In recent years, supervisory control schemes are incorporated in complex system aiming at preserving system reliability, operating safety and quality [1,2]. However, all these requirements are affected by the occurrence of faults, which typically emanate from: a) the wrong design and/or assembly, b) improper operation or missing maintenance, and c) the material aging, corrosion or wear during normal operation [3].…”