Distributed bounded-error state estimation based on practical robust positive invariance
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
In this paper we aim at controlling physically meaningful quantities with emphasis on environmental applications. This is carried out by an efficient numerical procedure combining the goal-oriented framework [R. Becker, R. Rannacher, An optimal control app ...
We pose the estimation of the parameters of multiple superimposed exponential signals in additive Gaussian noise problem as a Maximum Likelihood (ML) estimation problem. The ML problem is very non linear and hard to solve. Some previous works focused on fi ...
This paper focuses on distributed state estimation using a sensor network for monitoring a linear system. In order to account for physical constraints on process states and inputs, we propose a moving horizon approach where each sensor has to solve a quadr ...
A non-parametric method of distribution estimation for univariate data is presented. The idea is to adapt the smoothing spline procedure used in regression to the estimation of distributions via a scatterplot smoothing of theempirical distribution function ...
The sensitivity of the unmeasured state variables to the measurements strongly affects the rate of convergence of a state estimation algorithm. To overcome potential observability problems, the approach has been to identify the model parameters so as to re ...
This paper presents a novel distributed estimation algorithm based on the concept of moving horizon estimation. Under weak observability conditions we prove convergence of the state estimates computed by any sensor to the correct state even when constraint ...
