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An Efficient Indirect Identification Method for Feedback Control System

In many cases it is not possible to remove the feedback during an identification experiment because this may lead to instability. The feedback may also be inherent in many dynamic systems (e.g., economical, biological). In this paper we shall consider the problem of identification of dynamic systems operating under feedback control and propose an indirect approach to closed-loop system identification based on the bias-compensation principle. The main feature of the proposed method is that introductions of auxiliary vector and matrix are helpful to find an approach to estimating the noise-output correlated variance. Therefore via compensating the consistent bias of LS estimate, the consistent estimates for closed-loop system can be given.