Nonlinear unknown input observability and unknown input reconstruction: The general analytical solution

نویسندگان

چکیده

Observability is a fundamental structural property of any dynamic system and describes the possibility reconstructing state that characterizes from fusing observations its inputs outputs. Despite effort made to study this introduce analytical criteria capable verifying whether or not satisfies property, there no general criterion obtain observability when dynamics are also driven by unknown inputs. Here, we solution open problem, often called input problem. We provide systematic procedure, based on automatic calculation (differentiation determination matrix rank), which allows us check even in presence One ingredients characterization group invariance observability. have very recently introduced group, together with new set tensor fields respect transformations (Martinelli, 2020). The problem expressed terms these fields. In Martinelli (2020) provided restricting our investigation systems satisfy special assumption canonicity after an exhaustive concept canonicity, account for case satisfied solution. This form algorithm. addition, canonic dealt (2020), here result regards convergence properties Finally, as consequence results obtained here, condition reconstruct inputs, and, met, what can be reconstructed illustrate implementation algorithm studying nonlinear framework visual-inertial sensor fusion, whose two one known input. particular, system, follow step paper, solves most case.

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ژورنال

عنوان ژورنال: Information Fusion

سال: 2022

ISSN: ['1566-2535', '1872-6305']

DOI: https://doi.org/10.1016/j.inffus.2022.03.004