Parameter Estimation of Nonlinear Systems by Using Quadrature Kalman Filter

Abstract

In an estimation problem of the state or parameters in nonlinear systems, it is required to linearlize the original nonlinear system model. More recently, a statistical linear regression(SLR) method has been proposed for the linearlization. This technique is superior to Taylor series expansion-based ones.In this report, a method of treatment for the linearlization error arisen in the SLR linearization is proposed. Concretely, it is treated as a part of the state of the systems.A numerical experiment indicates acceptable performance of proposed method.