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Found 9 papers, 0 papers with code
Data-driven Dynamic Event-triggered Control
This paper revisits the event-triggered control problem from a data-driven perspective, where unknown continuous-time linear systems subject to disturbances are taken into account.
A Novel Dynamic Event-triggered Mechanism for Dynamic Average Consensus
This paper studies a challenging issue introduced in a recent survey, namely designing a distributed event-based scheme to solve the dynamic average consensus (DAC) problem.
On the Effects and Optimal Design of Redundant Sensors in Collaborative State Estimation
The paper presents two main results: a theoretical analysis of the effects of redundant sensors and an engineering-oriented optimal design of redundant sensors.
Observation of Periodic Systems: Bridge Centralized Kalman Filtering and Consensus-Based Distributed Filtering
This paper aims to consider the observation problem of periodic systems by bridging two fundamental filtering algorithms for periodic systems with a sensor network: consensus-on-measurement-based distributed filtering (CMDF) and centralized Kalman filtering (CKF).
Harmonic-Copuled Riccati Equations and its Applications in Distributed Filtering
This paper manages to formulate and investigate a new kind of coupled Riccati equations, called harmonic-coupled Riccati equations (HCRE), from the matrix iterative law of the consensus on information-based distributed filtering (CIDF) algortihm proposed in [1], where the solutions of the equations are coupled with harmonic means.
DiscreteCommunication and ControlUpdating in Event-Triggered Consensus
Noting that the existing related results only meeting one or two demands at most are essentially not applicable, in this paper we establish a novel framework to solve the problem of fully distributed consensus with discrete communication and control.
Minimal-order Appointed-time Unknown Input Observers: Design and Applications
Based on the reconstructed model, the minimal-order appointed-time unknown input observer is presented to realize state estimation of linear system with the unknown input at the arbitrarily small preset time.
Stochastic Event-triggered Variational Bayesian Filtering
This paper proposes an event-triggered variational Bayesian filter for remote state estimation with unknown and time-varying noise covariances.
Consensus-Based Distributed Filtering with Fusion Step Analysis
For consensus on measurement-based distributed filtering (CMDF), through infinite consensus fusion operations during each sampling interval, each node in the sensor network can achieve optimal filtering performance with centralized filtering.
