An Adaptive Non-Linearity Detection Algorithm for Process Control Loops

Non-linearities are considered to be a major source of oscillations and poor performance in industrial control systems, as 20-30 % of loops are reported to be oscillating due to valve non-linearities (Srinivasan et al. (2005)). This fact has led to a significant effort aimed at the detection and diagnosis of non-linearities; in particular for valve non-linearities in the control loops. The current paper presents an adaptive algorithm, based on HHT (Hilbert Huang Transform), for non-linearity detection and isolation in process systems. The HHT is an adaptive data analysis technique that is applicable to non-linear and non-stationary time series. An index termed the Degree of Non-Linearity (DNL), based on intra-wave frequency modulation, is used to identify the presence of non-linearity in the signal generating system. The proposed method is shown to be more robust in differentiating between linear and nonlinear causes of oscillations when compared to existing methods, and can handle non-stationary effects.