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Sparse Sensing and Optimal Precision: Robust H∞ Optimal Observer Design with Model Uncertainty | IEEE Conference Publication | IEEE Xplore

Sparse Sensing and Optimal Precision: Robust H∞ Optimal Observer Design with Model Uncertainty


Abstract:

We present a framework which incorporates three aspects of the estimation problem, namely, sparse sensor configuration, optimal precision, and robustness in the presence ...Show More

Abstract:

We present a framework which incorporates three aspects of the estimation problem, namely, sparse sensor configuration, optimal precision, and robustness in the presence of model uncertainty. The problem is formulated in the H∞ optimal observer design framework. We consider two types of uncertainties in the system, i.e. structured affine and unstructured uncertainties. The objective is to design an observer with a given H∞ performance index with minimal number of sensors and minimal precision values, while guaranteeing the performance for all admissible uncertainties. The problem is posed as a convex optimization problem subject to linear matrix inequalities. Numerical simulations demonstrate the application of the theoretical results presented in this work.
Date of Conference: 25-28 May 2021
Date Added to IEEE Xplore: 28 July 2021
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Conference Location: New Orleans, LA, USA

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