For a dynamic process identification throughout the whole operating range under diverse operating conditions, it is difficult to capture the process dynamics by a single process model in which the traditional identification method can be adopted to implement parameter estimation. By using the multiple dual-rate state-space models to approach the parameter-varying time-delay systems with different operating conditions, this paper explores an EM algorithm to simultaneously estimate the hidden variable, the parameter vector, the state variable and the time-delay by introducing hidden variables and by using a Kalman smoother.