Auto-Tuning of Frequency Sampling Filter Algorithm Using Step Response Data Analysis

Industries involved with process and manufacturing plants require a sound system and process to ensure the outcome of products they produce are of excellent quality, can be ready quickly, and consume minimal operating cost. Every process plant has measurement data that needs to be collected and analyzed from various machines and equipment. Obtaining a good model leading to good system control is essential for data-driven modeling. This paper uses automatic tuning for the frequency sampling filter algorithm for data analysis. The frequency sampling filter algorithm can analyze data and produce step and frequency response estimates, which can be used later for modeling and control. The automatic tuning method is required to avoid processing all raw data, leading to a long computational time. The steady-state error is used as the medium for tuning and checking how much data is required to represent the system sufficiently. The results show that the developed approach can process the data and provide step response estimates using less data. The reduction of processed data has reduced the overall computational time needed to analyze the data.