Fully Distributed Dynamic State Estimation With Uncertain Process Models
نویسندگان
چکیده
منابع مشابه
A framework for state-space estimation with uncertain models
This paper develops a framework for state-space estimation when the parameters of the underlying linear model are subject to uncertainties. Compared with existing robust filters, the proposed filters perform regularization rather than de-regularization. It is shown that, under certain stabilizability and detectability conditions, the steady-state filters are stable and that, for quadratically-s...
متن کاملDistributed State Estimation for Uncertain Markov-type Sensor Networks with Mode-dependent Distributed Delays
In this paper, the distributed state estimation problem is investigated for a class of sensor networks described by uncertain discrete-time dynamical systems with Markovian jumping parameters and distributed time-delays. The sensor network consists of sensor nodes characterized by a directed graph with a nonnegative adjacency matrix that specifies the interconnection topology (or the distributi...
متن کاملDistributed State Estimation for Hidden Markov Models with Dynamic Quantization and Rate Allocation
This paper considers state estimation of hidden Markov models by sensor networks. By employing feedback from the fusion center to the sensor nodes, a dynamic quantization scheme is proposed and analyzed by a stochastic control approach. Dynamic rate allocation is also considered. Copyright c ©2005 IFAC
متن کاملState estimation of linear dynamic system with unknown input and uncertain observation using dynamic programming
Abstract: The paper is devoted to deriving a novel estimation algorithm for linear dynamic system with unknown inputs when observations contain outliers. The algorithm is derived for arbitrary input signals and does not require a priori statistical information concerning input signals. The filtering problem is considered as a control problem in which the unknown input is regarded as a controlli...
متن کاملRecursive State Estimation for Distributed Parameter Uncertain Systems with Integral Quadratic Constraints
The problem of recursive state estimation for a class of distributed parameter systems with an integral quadratic constraint in Hilbert spaces is addressed. Based on solving the linear tracking problem for time-varying systems in Hilbert spaces, necessary and sufficient conditions for robust state estimation problem involving construction of the set of all possible states at the finite interval...
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: IEEE Transactions on Control of Network Systems
سال: 2018
ISSN: 2325-5870,2372-2533
DOI: 10.1109/tcns.2017.2763756