E3S Web Conf.
Volume 229, 2021The 3rd International Conference of Computer Science and Renewable Energies (ICCSRE’2020)
|Number of page(s)||5|
|Published online||25 January 2021|
Unknown Input Observer Design for a Class of Linear Descriptor Systems
Laboratory of High Energy Physics and Condensed Matter, Faculty of Science, Hassan II University of Casablanca. B.P 5366, Maarif, Casablanca, Morocco.
2 ECPI, Department of Electrical Engineering, ENSEM, Hassan II University of Casablanca. B.P 8118, Oasis, Casablanca, Morocco.
This paper addresses the problem of unknown inputs observer (UIO) design for a class of linear descriptor systems. The unknown inputs affect both state and output of the system. The basic idea of the proposed approach is based on the separation between dynamic and static relations in the descriptor model. Firstly, the method used to separate the differential part from the algebraic part is developed. Secondly, an observer design permitting the simultaneous estimation of the system state and the unknown inputs is proposed. The developed approach for the observer design is based on the synthesis of an augmented model which regroups the differential variables and unknown inputs. The exponential stability of the estimation error is studied using the Lyapunov theory and the stability condition is given in term of linear matrix inequality (LMI). Finally, to illustrate the efficiency of the proposed methodology, a heat exchanger pilot model is considered.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.