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.
منابع مشابه
Nonlinear Unknown Input Observability: Analytical expression of the observable codistribution in the case of a single unknown input
متن کامل
Nonlinear Unknown Input Observability: Extension of the Observability Rank Condition and the Case of a Single Unknown Input
This paper investigates the unknown input observability problem in the nonlinear case under the assumption that the unknown inputs are differentiable functions of time (up to a given order). The goal is not to design new observers but to provide simple analytic conditions in order to check the weak local observability of the state. The analysis starts by extending the observability rank conditi...
متن کاملPartial unknown input reconstruction for linear systems
The problem of partial unknown input (UI) reconstruction is addressed. It is considered that a linear functional of the UI vector has to be reconstructed using output information only. Necessary and sufficient conditions are given allowing for the reconstruction in finite time of the required UI’s; analogous conditions are obtained for the asymptotic reconstruction of the required UI’s. The sol...
متن کاملPassivity and Unknown Input Observers for Nonlinear Systems
The main objective of this work is to study the relationship between passivity and existence of UIO in the nonlinear case. This work is motivated by two facts: On the one side by the well-known relationship between passivity and robustness in control theory. On the other side the equivalence previously found by one of the authors in the linear (square) case between three concepts: existence of ...
متن کاملGeometric Insight and Structure Algorithms for Unknown-State, Unknown-Input Reconstruction in Linear Multivariable Systems
An algebraic approach to the synthesis of a dynamic system that reconstructs the generic inaccessible input of a discrete-time linear multivariable system with unknown initial state is discussed. The method devised exploits geometric properties of key subspaces for the original system and algebraic properties of the Moore-Penrose inverse of Toeplitz matrices related to the algorithms for comput...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Information Fusion
سال: 2022
ISSN: ['1566-2535', '1872-6305']
DOI: https://doi.org/10.1016/j.inffus.2022.03.004