Title :
Weighted estimation and tracking for ARMAX models
Author_Institution :
Lab. de Stat., Paris Univ., Orsay, France
Abstract :
For a complex multivariable ARMAX (autoregressive moving-average with exogeneous inputs) model, the author studies the weighted least squares algorithm which improves the usual least squares algorithm by the choice of suitable ponderations. Concerning adaptive tracking problems, both strong consistency of the estimator and control optimality are ensured
Keywords :
adaptive control; estimation theory; least squares approximations; matrix algebra; time series; tracking; ARMAX models; adaptive tracking; complex multivariable model; control optimality; strong consistency; weighted least squares algorithm; Adaptive control; Artificial intelligence; Convergence; Covariance matrix; Filtration; Least squares methods; Optimal control; Programmable control; Random variables; Trajectory;
Conference_Titel :
Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-0872-7
DOI :
10.1109/CDC.1992.371320
