Output Error Recursive Algorithms for Identification of Dual Youla-Kucera Models in Closed Loop Operation

Dual Youla-Kucera plant model parametrization is very useful for describing model uncertainties. Therefore it is interesting to develop recursive identification algorithms for identification of these type of plant model structures in closed loop operation for potential use in iterative tuning or adaptive control. Following the approach introduced in [1] closed loop output errors type recursive algorithms developed specifically for this type of model structure are presented. The algorithms assure global asymptotic stability in the deterministic environ-ment and unbiased parameter estimation in the presence of noise when the plant model is in the model set. The algorithms will be applied for the identification in closed loop of a test bench for active noise control.