A unified filter for simultaneous input and state estimation of linear discrete-time stochastic systems. (January 2016)

• Record Type: Journal Article
• Authors: Yong, Sze Zheng; Zhu, Minghui; Frazzoli, Emilio
• Is Part Of: Automatica. Volume 63(2016)
• Page Start: 321
• Page End: 329
• Publication Date: 2016-01
• Subjects: Optimal filtering -- State estimation -- Input estimation -- Filter stability -- Recursive filter; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2015.10.040
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: In this paper, we present a unified optimal and exponentially stable filter for linear discrete-time stochastic systems that simultaneously estimates the states and unknown inputs in an unbiased minimum-variance sense, without making any assumptions on the direct feedthrough matrix. We also provide the connection between the stability of the estimator and a system property known as strong detectability, and discuss the global optimality of the proposed filter. Finally, an illustrative example is given to demonstrate the performance of the unified unbiased minimum-variance filter.