9 citations · 32 across the 19 of their papers we have counts for
12 papers · 1 filter
Reinforcement Learning Approach to Estimation in Linear Systems
Minyue Fu
This paper addresses two important estimation problems for linear systems, namely system identification and model-free state estimation. Our focus is on ARMAX models with unknown p…
Distributed Kalman Estimation with Decoupled Local Filters
Damián Marelli, Tianju Sui, Minyue Fu
We study a distributed Kalman filtering problem in which a number of nodes cooperate without central coordination to estimate a common state based on local measurements and data re…
Convergence Rate of a Message-passing Algorithm for Solving Linear Systems
Zhaorong Zhang, Qianqian Cai, Minyue Fu
This paper studies the convergence rate of a message-passing distributed algorithm for solving a large-scale linear system. This problem is generalised from the celebrated Gaussian…
Convergence and Accuracy Analysis for A Distributed Static State Estimator based on Gaussian Belief Propagation
Damián Marelli, Tianju Sui, Minyue Fu +1
This paper focuses on the distributed static estimation problem and a Belief Propagation (BP) based estimation algorithm is proposed. We provide a complete analysis for convergence…
Distributed Weighted Least-squares Estimation for Networked Systems with Edge Measurements
Qiqi Yang, Zhaorong Zhang, Minyue Fu
This paper studies the problem of distributed weighted least-squares (WLS) estimation for an interconnected linear measurement network with additive noise. Two types of measurement…
The Vulnerability of Cyber-Physical System under Stealthy Attacks
Tianju Sui, Yilin Mo, Damián Marelli +2
In this paper, we study the impact of stealthy attacks on the Cyber-Physical System (CPS) modeled as a stochastic linear system. An attack is characterised by a malicious injection…
Statistical Approach to Detection of Attacks for Stochastic Cyber-Physical Systems
Damián Marelli, Tianju Sui, Minyue Fu +1
We study the problem of detecting an attack on a stochastic cyber-physical system. We aim to treat the problem in its most general form. We start by introducing the notion of asymp…
Multi-sensor State Estimation over Lossy Channels using Coded Measurements
Tianju Sui, Damian Marelli, Ximing Sun +1
This paper focuses on a networked state estimation problem for a spatially large linear system with a distributed array of sensors, each of which offers partial state measurements,…
A Distributed Adaptive Scheme for Multi-Agent Systems
Imil Hamda Imran, Zhiyong Chen, Lijun Zhu +1
In traditional adaptive control, the certainty equivalence principle suggests a two-step design scheme. A controller is first designed for the ideal situation assuming the uncertai…
Mean-square Stabilizability via Output Feedback for Non-minimum Phase Networked Feedback Systems
Weizhou Su, Jieying Lu, Yilin Wu +2
This work studies mean-square stabilizability via output feedback for a networked linear time invariant (LTI) feedback system with a non-minimum phase plant. In the feedback system…
Stability of Kalman Filtering with a Random Measurement Equation: Application to Sensor Scheduling with Intermittent Observations
Damián Marelli, Tianju Sui, Eduardo Rohr +1
Studying the stability of the Kalman filter whose measurements are randomly lost has been an active research topic for over a decade. In this paper we extend the existing results t…
Distributed Kalman Filter in a Network of Linear Dynamical Systems
Damian Marelli, Mohsen Zamani, Minyue Fu
This paper is concerned with the problem of distributed Kalman filtering in a network of interconnected subsystems with distributed control protocols. We consider networks, which c…