1. A method of model identification for a process with unknown initial conditions in an industrial plant, the method comprising: collecting a set of manipulated variables and a corresponding set of process variables from the process, the manipulated variables being sent from a controller to the process for adjusting each process variable to reach a set-point, the set point being a desired value for each process variable, each process variable being obtained by a sensor provided in the process; obtaining a plurality of manipulated variables from the collected set of manipulated variables; for each of the plurality of manipulated variables, obtaining optimal model parameters of a model transfer function and computing a model fitting index for optimized simulated process variables generated by the model transfer function using the optimal model parameters; identifying a best model fitting index among the model fitting indices computed; selecting a manipulated variable associated with the best model fitting index as an initial steady state condition for the model transfer function; and selecting the optimal model parameters corresponding with the best model fitting index as the best model parameters of the model transfer function to tune the controller.