Closed-loop Identification and Dead Time Estimation Based on Generalized Minimum Variance Evaluation

This paper provides a closed-loop identification method based on generalized minimum variance (GMV) evaluation in the case where the system has an unknown dead time. The proposed method searches for candidates over a prescribed set of the dead time and obtains an optimal solution for the system model. The paper also gives a new variance criterion and shows that its optimization results in the unique optimal solution, corresponding to the actual system parameters and the actual dead-time. The proposed criterion consists of routine operation data, and it is computable without any experiments for the identification. A simulation result shows the efficiency of the proposed method.