Brief paper: Recursive estimation of the parameters of linear multivariable systems

Authors:
N. K. Sinha;Y. H. Kwong
Affiliations:
Group on Simulation, Optimization & Control, Faculty of Engineering, McMaster University, Hamilton, Ontario, Canada L8S 4L7;Y. H. Kwong, Algoma Steel Company, Sault Ste. Marie, Ontario, Canada
Venue:
Automatica (Journal of IFAC)
Year:
1979

Citing 1
Cited 4

Canonical structures in the identification of multivariable systems

Automatica (Journal of IFAC)

Multi-innovation stochastic gradient algorithms for multi-input multi-output systems

Digital Signal Processing
On the value of information in system identification-Bounded noise case

Automatica (Journal of IFAC)
Hierarchical gradient-based identification of multivariable discrete-time systems

Automatica (Journal of IFAC)
On the identification of continuous-time multivariable systems from samples of input-output data

Mathematical and Computer Modelling: An International Journal

Quantified Score

Hi-index	22.15

Visualization

Abstract

A recursive algorithm is proposed for the identification of linear multivariable systems. Utilization of a canonical state space model minimizes the number of parameters to be estimated. The problem of identification in the presence of noise is solved by using a recursive generalized least-squares method.