ON DISTURBANCE ESTIMATION AND ITS APPLICATIONS IN HEALTH MONITORING

This research focuses on the disturbance estimation problem. A survey of existing techniques is first conducted, where extensive plant knowledge for state estimation is contrasted with less plant knowledge for disturbance estimation. To advance the latter methodology and to reduce over-dependence on model information in the former, the boundary between a model and disturbance is redrawn. With this redefined boundary, existing methods are improved. Furthermore, to make the estimators optimal as well as practical, a new concept of practical optimality is introduced. Several novel design techniques are developed and initial results show advantages over current disturbance estimators. Finally, the disturbance estimation techniques are applied to health monitoring of dynamic systems. Two engineering examples are used to demonstrate the effectiveness and practicality of the new methods, including the health monitoring of a servomechanism and the fault diagnosis of a three-tank level control system.

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