MODEL WEIGHT AND STATE ESTIMATION FOR MULTIPLE MODEL SYSTEMS APPLIED TO FAULT DETECTION AND IDENTIFICATION

Abstract A method is proposed for estimating both the weights and the state of a multiple model system with one common state vector. In this system, the weights are related to the activation of each individual model. For the resulting nonlinear estimation problem a method is developed that efficiently decomposes the total problem into two separate parts, one for estimating the model weights and one for estimating the state. The method has been validated on a component, actuator and sensor fault detection and identification problem for a linearized model of an aircraft.

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