System identification for nonlinear FOPDT model with input-dependent dead-time

An on-line iterative method of system identification for a kind of nonlinear FOPDT system is proposed in the paper. The considered nonlinear FOPDT model is an extension of the standard FOPDT model by means that its dead time depends on the input signal and the other parameters are time dependent. In order to identify these parameters in an online manner, the considered system is discretized at first. Then, the nonlinear FOPDT identification problem is formulated as a stochastic Mixed Integer Non-Linear Programming problem, and an identification algorithm is proposed by combining the Branch-and-Bound method and Mean Least Square technique. The proposed method is tested through a number of numerical examples. As shown in the case studies, the proposed method can provide a reasonable performance in the parameters identification with regard to the reasonable accuracy. The result also showed that the dead time change according to the input can also be reasonable tracked.