@article{Byrski_Byrski_2018, title={State estimators and observers for continuous and discrete linear systems: Part 1. Differential asymptotic state estimators}, volume={3}, url={https://journals.anstar.edu.pl/index.php/sti/article/view/243}, DOI={10.5604/01.3001.0012.8169}, abstractNote={<p>In the paper an overview of state estimators and state observers used in linear systems, will be presented. The state estimators and observers can be used in many applications like the state reconstruction for the control purposes or for the diagnosis and fault detection in technical processes or for the virtual measurements of inaccessible variables of the system as well as for the best filtration of the differential equation solution. As the standard most commonly the Kalman filter and Luenberger type observers are used. Although the Kalman filter guarantees optimal filtering quality of the state, reconstructed from the noisy measurements, both Kalman filter and the Luenberger observer guarantee only asymptotic quality of the real state changes and tracking, basing on the current measurements of the system output and input signals. Unfortunately, the value of the estimation error at any moment of time cannot be calculated. The discussion on differences between continuous and two types of discrete Kalman Filter will be presented. This paper is plan to be the introduction to presentation of the another type of the state observers which have the structure given by the integral operators. Based on measurements of the system output and input signals on some predefined finite time interval, they can reconstruct, after this interval, the observed state exactly.</p>}, number={2}, journal={Science, Technology and Innovation}, author={Byrski, Jędrzej and Byrski, Witold}, year={2018}, month={Dec.}, pages={62–68} }