Title :
An order downdating algorithm for tracking system order and parameters in recursive least squares identification
Author :
Apley, Daniel W. ; Shi, Jianjun
Author_Institution :
Dept. of Ind. Eng., Texas A&M Univ., College Station, TX, USA
fDate :
11/1/1999 12:00:00 AM
Abstract :
A new time and order recursive method for on-line tracking of system order and parameters using recursive least squares (RLS) is presented. The method consists of two parts: a time updating portion that uses existing RLS inverse QR decomposition algorithms and a new computationally efficient “order downdating” portion that calculates the model parameters and residual error energies for an entire set of models with order varying from one to some prespecified maximum model order
Keywords :
error analysis; least squares approximations; matrix decomposition; matrix inversion; recursive estimation; spectral analysis; tracking; RLS inverse QR decomposition algorithms; computationally efficient order downdating; inverse QR factorization; model parameters; order downdating algorithm; recursive least squares identification; residual error energies; spectral estimation; system order tracking; system parameters tracking; time updating; Adaptive control; Least squares approximation; Least squares methods; Recursive estimation; Resonance light scattering; Robots; Signal processing algorithms; Solid modeling; System identification; Time varying systems;
Journal_Title :
Signal Processing, IEEE Transactions on
