Title :
A recursive algorithm for ARMAX model identification in closed loop
Author :
Landau, I.D. ; Karimi, A.
Author_Institution :
Lab. d´´Autom. de Grenoble, CNRS, St. Martin d´´Heres, France
fDate :
4/1/1999 12:00:00 AM
Abstract :
The joint problem of the recursive estimation of an optimal predictor for the closed-loop system and the unbiased parameter estimation of an ARMAX plant model in closed-loop operation is considered. A special reparameterized optimal predictor for the closed-loop is introduced. This allows a parameter estimation algorithm for the plant model to be derived which is globally asymptotically stable in a deterministic environment and gives asymptotically unbiased parameters estimates under richness conditions
Keywords :
autoregressive moving average processes; closed loop systems; optimisation; prediction theory; recursive estimation; ARMAX model identification; closed-loop system; globally asymptotically stable algorithm; optimal predictor; recursive estimation; reparameterized optimal predictor; unbiased parameter estimation; Adaptive systems; Asymptotic stability; Context modeling; Error correction; Open loop systems; Parameter estimation; Predictive models; Recursive estimation; Robust control; Working environment noise;
Journal_Title :
Automatic Control, IEEE Transactions on
