Framework for state and unknown input estimation of linear time-varying systems. (November 2016)

• Record Type: Journal Article
• Authors: Lu, Peng; van Kampen, Erik-Jan; de Visser, Cornelis C.; Chu, Qiping
• Is Part Of: Automatica. Volume 73(2016)
• Page Start: 145
• Page End: 154
• Publication Date: 2016-11
• Subjects: Kalman filtering -- State estimation -- Unknown input filtering -- Fault estimation -- Double-Model Adaptive Estimation; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2016.07.009
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: The design of unknown-input decoupled observers and filters requires the assumption of an existence condition in the literature. This paper addresses an unknown input filtering problem where the existence condition is not satisfied. Instead of designing a traditional unknown input decoupled filter, a Double-Model Adaptive Estimation approach is extended to solve the unknown input filtering problem. It is proved that the state and the unknown inputs can be estimated and decoupled using the extended Double-Model Adaptive Estimation approach without satisfying the existence condition. Numerical examples are presented in which the performance of the proposed approach is compared to methods from literature.