Iterative Hybrid Identification of Spatial Bilinear Models in the Presence of Uncertainty
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This paper introduces the concept of a novel spatial model identification procedure which makes use of a hybrid combination of two algorithms implemented in an iterative manner. The approach is shown to provide effective results in the presence of uncertainty and absence of an ideal quantity of data. The potential practicability of the approach is highlighted in the context of the development of active control of collision energy absorption.
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