The two-stage recursive extended least squares parameter estimation algorithm based on the auxiliary model of a class of closed-loop identification system model is presented in this paper. The basic idea of the algorithm is a combination of the auxiliary model identification ideas and the decomposition technique in which the closed-loop system is converted to a two-step process and each step identified model is an open-loop system. The more mature open-loop identification method is dealt with, the closed-loop system parameter identification problem is known in this way. The proposed algorithm has been proven to have high computational efficiency and effectiveness by the simulation examples.
Key words: Auxiliary model, least squares method, closed-loop system.
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