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

Multiple Model Adaptive Control Using Dual Youla-Kucera Factorisation

We propose a multi-model adaptive control scheme for uncertain linear plants based on the concept of model unfalsification. The approach relies on examining the ability of a precomputed set of plant-controller candidates and choosing the one that is best able to reproduce observed inand output signal samples. The ability to reproduce observations is measured as an easily computable signal norm....

A Youla-Kucera parametrized adaptive feedforward compensator for active vibration control with mechanical coupling

Most of the adaptive feedforward vibration (or noise) compensation systems feature an internal ”positive feedback” coupling between the compensator system and the correlated disturbance measurement which serves as reference. This may lead to the instability of the system. Instead of the standard IIR structure for the adaptive feedforward compensator, the paper proposes a Youla-Kucera parametriz...

From Youla-Kucera to Identification, Adaptive and Nonlinear Control

A recursive algorithm for ARMAX model identification in closed loop

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 ...

Recursive identification algorithms for continuous-time nonlinear plants operating in closed loop

A family of algorithms for the identification of continuous-time nonlinear plants operating in closed loop is presented. An adjustable closed-loop output error-type predictor parameterized in terms of the existing controller and the estimated plant model is used. The algorithms are derived from stability considerations in the absence of noise and assuming that the plant model is in the model se...