INDIRECT IDENTIFICATION OF LINEAR STOCHASTIC-SYSTEMS WITH KNOWN FEEDBACK DYNAMICS

An algorithm is presented for identifying a state-space model of linea r stochastic systems operating under known feedback controller. In thi s algorithm, only the reference input and output of closed-loop data a re required. No feedback signal needs to be recorded. The overall clos ed-loop system dynamics is first identified. Then a recursive formulat ion is derived to compute the open loop plant dynamics from the identi fied closed-loop system dynamics and known feedback controller dynamic s. The controller can he a dynamic or constant-gain full-state feedbac k controller. Numerical simulations and test data of a highly unstable large-gap magnetic suspension system are presented to demonstrate the feasibility of this indirect identification method.