Reduced Bank of Kalman Filters
نویسنده
چکیده
A reduction of the computational complexity of bank of Kalman filters is proposed. The algorithm is focused in fault detection and isolation problems. It is shown that the orders of individual filters in the bank can be lower than the respective filtered process model order. The original model state variables are not estimated. Linear functions of noise samples are the newly estimated variables.
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تاریخ انتشار 2008