Abstract:
This work presents a novel general regularized distributed solution for the state estimation problem in networked systems. Resting on the graph-based representation of se...Show MoreMetadata
Abstract:
This work presents a novel general regularized distributed solution for the state estimation problem in networked systems. Resting on the graph-based representation of sensor networks and adopting a multivariate least-squares approach, the designed solution exploits the set of the available inter-sensor relative measurements and leverages a general regularization framework, whose parameter selection is shown to control the estimation procedure convergence performance. As confirmed by the numerical results, this new estimation scheme allows ( i ) the extension of other approaches investigated in the literature and ( ii ) the convergence optimization in correspondence to any (undirected) graph modeling the given sensor network.
Published in: IEEE Control Systems Letters ( Volume: 6)
Funding Agency:
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Relative Measure ,
- System State Estimation ,
- Numerical Results ,
- Parameter Selection ,
- Undirected ,
- Sensor Networks ,
- Convergence Performance ,
- Eigenvalues ,
- Sufficient Conditions ,
- Regularization Parameter ,
- Optimal Selection ,
- Largest Eigenvalue ,
- Laplacian Matrix ,
- Update Rule ,
- Graph Topology ,
- Degree Matrix ,
- Norm Minimization ,
- Small-world Network ,
- Domain Parameters ,
- Spectrum Of Matrix ,
- Real Spectrum ,
- Regular Matrix ,
- Regular Graphs ,
- Cut Set ,
- Graph-based Models ,
- Convergence Of Scheme ,
- Largest Eigenvalue Of Matrix ,
- Diagonal Matrix ,
- Node Status ,
- State Matrix
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Relative Measure ,
- System State Estimation ,
- Numerical Results ,
- Parameter Selection ,
- Undirected ,
- Sensor Networks ,
- Convergence Performance ,
- Eigenvalues ,
- Sufficient Conditions ,
- Regularization Parameter ,
- Optimal Selection ,
- Largest Eigenvalue ,
- Laplacian Matrix ,
- Update Rule ,
- Graph Topology ,
- Degree Matrix ,
- Norm Minimization ,
- Small-world Network ,
- Domain Parameters ,
- Spectrum Of Matrix ,
- Real Spectrum ,
- Regular Matrix ,
- Regular Graphs ,
- Cut Set ,
- Graph-based Models ,
- Convergence Of Scheme ,
- Largest Eigenvalue Of Matrix ,
- Diagonal Matrix ,
- Node Status ,
- State Matrix
- Author Keywords