Title :
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
fDate :
8/1/2001 12:00:00 AM
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;
Conference_Titel :
Instrumentation in Aerospace Simulation Facilities, 2001. 19th International Congress on ICIASF 2001
Conference_Location :
Cleveland, OH
Print_ISBN :
0-7803-7022-8
DOI :
10.1109/ICIASF.2001.960271
