Sensor Selection and Optimal Precision in $\mathcal{H}_2/\mathcal{H}_{\infty}$ Estimation Framework: Theory and Algorithms
Systems and Control
2021-04-08 v2 Systems and Control
Optimization and Control
Abstract
We consider the problem of sensor selection for designing observer and filter for continuous linear time invariant systems such that the sensor precisions are minimized, and the estimation errors are bounded by the prescribed performance criteria. The proposed integrated framework formulates the precision minimization as a convex optimization problem subject to linear matrix inequalities, and it is solved using an algorithm based on the alternating direction method of multipliers (ADMM). We also present a greedy approach for sensor selection and demonstrate the performance of the proposed algorithms using numerical simulations.
Cite
@article{arxiv.2103.00750,
title = {Sensor Selection and Optimal Precision in $\mathcal{H}_2/\mathcal{H}_{\infty}$ Estimation Framework: Theory and Algorithms},
author = {Vedang M. Deshpande and Raktim Bhattacharya},
journal= {arXiv preprint arXiv:2103.00750},
year = {2021}
}