Comparison of six on-line identification and parameter estimation methods
Automatica (Journal of IFAC)
IFAC congress survey paper: Identification in automatic control systems
Automatica (Journal of IFAC)
Comparison of different methods for identification of industrial processes
Automatica (Journal of IFAC)
System identification-A survey
Automatica (Journal of IFAC)
An instrumental variable method for real-time identification of a noisy process
Automatica (Journal of IFAC)
On-line identification of a class of non-linear systems from noisy measurements
Automatica (Journal of IFAC)
Analysis of a general recursive prediction error identification algorithm
Automatica (Journal of IFAC)
Comparison of six on-line identification and parameter estimation methods
Automatica (Journal of IFAC)
Special section system identification tutorial: Practical aspects of process identification
Automatica (Journal of IFAC)
Paper: Recursive output error identification algorithms theory and evaluation
Automatica (Journal of IFAC)
Paper: A theoretical analysis of recursive identification methods
Automatica (Journal of IFAC)
Paper: Experimental comparison and application of various parameter-adaptive control algorithms
Automatica (Journal of IFAC)
| Hi-index | 22.16 |
This paper discusses six popular parameter identification algorithms developed mainly for linear discrete-time dynamic systems. They are namely the Crosscorrelation technique, the first and second Stochastic Approximation methods, the Maximum Likelihood method, the Maximum a-posteriori probability filter, and the extended Kalman filter. Their computational properties are compared and their convergence is tested on two fourth order discrete-time systems. An overall evaluation of the methods is also presented.