Unbiased minimum-variance input and state estimation for systems with unknown inputs: A system reformation approach. (October 2017)

• Record Type: Journal Article
• Authors: Hsieh, Chien-Shu
• Is Part Of: Automatica. Volume 84(2017)
• Page Start: 236
• Page End: 240
• Publication Date: 2017-10
• Subjects: Unbiased minimum-variance estimation -- Unknown input filtering -- Optimal input and state estimation -- System reformation; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2017.06.037
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: This paper presents a system reformation based unbiased minimum-variance input and state estimation for systems with unknown inputs which can be reconstructed with a one-step delay. It is shown that, within this new filtering approach the optimal unknown input and state estimation can be simultaneously achieved through the filter developed by Gillijns and De Moor. An illustrative example is given to show the effectiveness of the proposed results. Moreover, under some additional assumptions the proposed system reformation can be easily extended to consider a multi-step delayed input estimation.