IDENTIFICATION OF STOCHASTIC-SYSTEM AND CONTROLLER VIA PROJECTION FILTERS

A method based on projection filters is presented for identifying an o pen-loop stochastic system with an existing feedback controller. The p rojection filters are derived from the relationship between the state- space model and the AutoRegressive with ASME exogeneous input (ARX) mo del including the system, Kalman filter and controller. Two ARX models are identified from the control input, closed-loop system response an d feedback signal using least-squares method Markov parameters of the open-loop system, Kalman filter and controller are then calculated fro m the coefficients of the identified ARX models. Finally, the state-sp ace model of the open-loop stochastic system and the gain matrices for the Kalman filter and controller are realized The method is validated by simulations and test data from an unstable large-angle magnetic su spension test facility.