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The direction of the roads affects significantly how much the multiple model filters would gain from the on-road model.
It is used as a design model at pre-fault for one of the multiple model filters used for fault diagnosis.
Similarly, the sensitivity to the transition probabilities used in multiple model filters proves to be less important compared to the gain obtained by using an additional on-road model.
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Since the different road segments correspond to different modes in these IMM algorithms, there are too many of them to be considered at a single step of the multiple model filter.
This paper provides justification and implementation for a multiple model filtering approach to diagnosis of transmission line three-phase short to ground faults in the presence of protection misoperations.
Multiple-model filtering is only used to smooth motion parameters b 0 and b 1 to reduce the necessary number of modes.
The proposed constrained multiple-model filter is able to generate more balanced results, which is consistent with our observation and analysis in Section 5.1.
The multiple-model filtering method [34, 35] is applied to fault mode diagnosis for the 9-bus system equipped with a network of 3 PMU-like sensors in [22].
Remark 6 (Other Multiple Model Particle Filters) There are other instances of multiple model particle filters in the literature [7, 36].
The state of the art multiple model particle filters are used with two different models, namely, an on-road (road-constrained) model and an off-road (unconstrained) model to perform tracking in 3D global coordinates.
In order to compare the performance of different multiple model particle filters, and different mode transition probabilities in a controlled manner, a Monte-Carlo simulation based on synthetic data is presented in this section.
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