Approximated unbiased minimum-variance simultaneous states and parameters estimation for nonlinear systems. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Ishihara, Shinji; Yamakita, Masaki
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 1607
• Page End: 1612
• Publication Date: 2017-07
• Subjects: Nonlinear filters -- Parameter estimation -- State estimation -- Nonlinear sysytems -- Uncertain dynamic systems; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.318
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This paper addresses joint state and parameter estimation problem for nonlinear systems. We linearize the nonlinear system by unscented statistical linearization (USL) and decouple unknown parameter vector of state vector. Then, we treat unknown parameter vector as unknown inputs to the approximated linear model. Furthermore, we applied unbiased minimum variance estimation (UMVE) method for the approximated linear system with unknown input. Our proposed method also offers an easy way to apply the UMVE to nonlinear systems. We confirm the validity of the proposed methods by Monte Carlo simulations.