Reinforcing Hurst Exponent with Oscillation Detection for Control Performance Analysis: An Industrial Application

Control performance assessment is one of the most important components of control assets monitoring. In the past decades, many different data-based approaches have been presented to assess control performance. Due to the high number of control loops for production industries, the methods requiring less parameters and less priori information became popular in industrial use. Detrended Fluctuation Analysis (DFA) is one of these methods, requiring only closed loop data and a pair of segment length to estimate Hurst exponent based control performance. However, the selection of segment lengths plays an important role in estimation, especially for oscillating control loops. In this paper, we have proposed an additional step (i.e. a step zero) to DFA to estimate control performance. This step uses an autocorrelation based and robust oscillation detection and characterization method to identify the oscillation period. Then, the calculated period is used to select the minimum segment length which leads more robust and precise estimation of control performance based on DFA. The proposed method has been applied and tested on several industrial control loops. The comparisons of the results between two approaches are given.