Multi-sensor state estimation using SDRE information filters

Chandra, KPB; Kothari, M; Gu, D-W; Postlethwaite, I

doi:10.3182/20140824-6-ZA-1003.01998

Multi-sensor state estimation using SDRE information filters

Lookup NU author(s): Emeritus Professor Ian Postlethwaite

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.

Abstract

© IFAC.This paper presents a derivative free state estimation algorithm for nonlinear systems called the state dependent Riccati equation information filter (SDREIF). The SDREIF is developed by fusing an SDRE filter with an information filter. Similar to the extended Kalman filter (EKF) or the extended information filter (EIF), the proposed SDREIF consists of two stages, prediction and update. However, unlike the EKF or EIF, the SDREIF does not use Jacobians and hence the filter is suitable for highly nonlinear systems. Furthermore, the framework is extended to handle state estimation for multi-sensor measurements. The efficacy of the proposed SDREIF is shown by a simulation example of a permanent magnet synchronous motor.