A Two Stage Identification Approach for Processes with Dead-time using Step Input

This work deals with the identification of unknown delayed systems as continuous-time models with dead-time. The identification experiment involves the collection of data samples with the application of step input, which is popular due to its simplicity. The gain elimination method is employed to bring dead-time into the parameter vector. The model parameters are estimated using two stage identification approach, where the first stage is simple least square and the second stage is instrument variable. The over-parameterized information vectors are computed using filtered derivatives. Simulation experiments are performed on benchmark systems to validate and compare the efficacy of the proposed approach with sensor noise.