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This paper considers the worst-case estimation problem in the presence of unknown but bounded noise. Contrary to stochastic approaches, the goal here is to confine the estimation error within a bounded set. Previous work dealing with the problem has shown that the complexity of estimators based upon the idea of constructing the state consistency set (e.g. the set of all states consistent with the...
In this paper the indoor wireless localization problem is addressed both from the theoretical and application standpoints. The main result of the paper is on the theoretical side: the topological definition of regular and irregular nodes is introduced, and formal results are presented to support regularity as a desirable network property for the attainment of precise node localization. In force of...
In this paper a fully decentralized algorithm for indoor wireless localization is presented. The algorithm combines the use of convex and non-convex optimization procedures, nested to achieve better converge towards the best positioning of a multitude of blind wireless nodes. The algorithm proceeds locally on each node, based on the sole knowledge of the measured distances from, and estimated positions...
This paper presents a continuous time solution to the problem of the design of a relatively optimal control, precisely, a dynamic control which is optimal with respect to a given initial condition and it is stabilizing for any other initial state. This technique provides a drastic reduction of the complexity of the controller and successfully applies to systems in which (constrained) optimality is...
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