Estimation of First Order Plus Dead Time and Second Order Plus Dead Time models from noisy step response data

This paper proposes the estimation of first-order-plus-dead-time (FOPDT) and second-order-plus-dead-time (SOPDT) models from noisy step response data. The model parameters are estimated by computation of areas, which makes it robust in the presence of stochastic disturbances in the step response data. The efficiency of the methodology is extensively tested in various numerical examples as well as in real-life experimental tests. The results-comparing our proposed estimation method with some other methods-suggest that the novel algorithm can be used with noisy step response data and adequately approximates high-order systems. Moreover, it does not require any system identification expertise, making it readily accessible for the nonexperienced user in industrial practice. The method is successfully validated for overdamped, reasonably underdamped, as well as highly oscillatory processes, hence offering a comprehensive estimation method.