摘要：AbstractThis paper develops a closed-loop subspace identification algorithm for the systems with the stochastic part possessing zeros close to the unit circle. The proposed algorithm estimates the system under the feedback loop, taking the effect of the initial state into account. A nonlinear optimization technique is applied for computing the Kalman gain and the covariance of the innovation. Numerical simulation shows that the proposed algorithm successfully provides models by taking the initial effect.
关键词：Keywordsclosed-loop subspace identificationstochastic subspace identificationstochastic realizationKalman gaincovariance of innovation
