Identification of system dynamics in presence of measurement noise

A technique for identification of system dynamics under the influence of measurement noise is presented. When output signal from sensor is corrupted by noise, identification of system parameters become an arduous task. Therefore, denoising methods can be employed in order to achieve a clean limit cycle under noisy environment. A Fast Fourier Transform (FFT) method has been reported as an effective technique for the mitigation of noise by an appropriate thresholding. Generalized explicit expressions are examined to obtain unknown plant model parameters for stable and unstable First Order Plus Dead Time (FOPDT) processes. Examples are illustrated to show the effectiveness of method during parametric identification of process models. Subsequently, a comparison is drawn between estimated and actual system through simulation by step test and Nyquist plot.