Recursive algorithms for identification of dual Youla-Kucera parametrized plant models in closed loop

The growing interest in using dual Youla Kucera plant parametrization for modeling uncertainties raises the need recursive identification algorithms dedicated to of these structures closed loop view developing appropriate iterative tuning and adaptive control strategies. paper presents Youla-Kucera parametrized models. These assure global asymptotic stability deterministic environment allow obtain unbiased parameter estimation presence measurement noise when model is set. also re-visit Hansen scheme which allows associate open type loop. When not set, comparison various done terms bias distribution. Further comparisons performance evaluation provided by simulations on some relevant examples experimental a test bench active control.