Automatic oscillations detection and quantification in process control loops using linear predictive coding

Oscillations in control loops are very common and primarily responsible for product quality variations and therefore may reduce profitability of the plant. Further, there can also be multiple oscillations at the same time due to multiple sources such as improper tuned controllers, disturbances and nonlinearity etc. Detection and estimation of oscillation is desired for their effective compensation which becomes a challenging task particularly in presence of noise. This paper presents a novel oscillation detection method based on linear predictive coding (LPC). In the proposed technique roots of the linear predictive polynomial are used to detect the oscillations. Further, for the quantification spectrum of cross-correlation of linear predictive residual and original data is used. The effectiveness of the proposed oscillation detection technique has been demonstrated with several simulation examples and actual plant data. The comparative investigation with the empirical mode decomposition method, generally employed for this task, revealed that proposed technique is simple, fast, robust and capable of handling slow varying trends. Keywords: Oscillation detection, Linear predictive coding, Stiction, Linear predictive polynomial, Cross-correlation

Abstract licence: CC BY-NC-ND

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