Time varying parameter estimation with decomposition system

Author

An, Andrew ; Huang, Junqin ; Shimada, Yuzo ; Ming, Qu ; Youxin, Yuan

Author_Institution

Beijing Univ. of Aeronaut. & Astronaut., China

fYear

2001

fDate

8/1/2001 12:00:00 AM

Firstpage

360

Lastpage

368

Abstract

This paper presents an algorithm for on line parameter estimation with decomposition of MIMO linearized time varying system. The test data is the process and measurement noise. Generally speaking, the former online parameter estimation method for MIMO system needed either normalizing the system math model or a lot of calculation for inverse matrix in estimating processing. It is not only takes much operational time, but also easily diverges when the matrix is irreversible. The method that we present here hierarchically estimates parameters so that can avoid the inverse matrix and follow the time varying parameter step by step. That could raise the calculation precision and ensure the proceeding convergence. Using the simulation flight test data in processing and measurement noise, the method has been examined

Keywords

Kalman filters; MIMO systems; adaptive control; aircraft control; convergence of numerical methods; matrix decomposition; recursive estimation; time-varying systems; Kalman Filter; MIMO linearized time varying system; adaptive control system; convergence; cost function; decomposition system; flight test data; hierarchical parameter identification; inverse matrix; on line parameter estimation; time varying parameter estimation; Aerospace simulation; Convergence; Covariance matrix; Extraterrestrial measurements; MIMO; Matrix decomposition; Noise measurement; Parameter estimation; Testing; Time varying systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation in Aerospace Simulation Facilities, 2001. 19th International Congress on ICIASF 2001

Conference_Location

Cleveland, OH

Print_ISBN

0-7803-7022-8

Type

conf

DOI

10.1109/ICIASF.2001.960271

Filename

960271