Title :
Adaptive control of parametric nonlinear autoregressive models via a new martingale approach
Author :
Bercu, Bernard ; Portier, Bruno
Author_Institution :
Lab. de Mathematiques, Univ. de Paris-Sud, Orsay, France
fDate :
9/1/2002 12:00:00 AM
Abstract :
The purpose of this note is to investigate the stability and the optimality of the adaptive tracking for a wide class of parametric nonlinear autoregressive models, via a new martingale approach. Several asymptotic results for the standard least squares estimator of the unknown model parameter, such as a central limit theorem, a law of iterated logarithm, and strong laws of large numbers are also provided.
Keywords :
adaptive control; autoregressive processes; stability; adaptive control; adaptive tracking; central limit theorem; law of iterated logarithm; least squares estimator; martingale; optimality; parametric nonlinear autoregressive models; stability; Adaptive control; Asymptotic stability; Centralized control; Convergence; Least squares approximation; Least squares methods; Polynomials; Power system modeling; Stability analysis; Trajectory;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2002.802756
