NN-based algorithm for control valve stiction quantification
WSEAS Transactions on Systems and Control
Development of quantification algorithm for control valve stiction
ISPRA'09 Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation
Valve stiction detection using NLPCA
MIC '08 Proceedings of the 27th IASTED International Conference on Modelling, Identification and Control
Brief paper: Applying neuro-fuzzy model dFasArt in control systems
Engineering Applications of Artificial Intelligence
Hi-index | 22.14 |
Higher-order statistical (HOS) techniques were first proposed over four decades ago. This paper is concerned with higher-order statistical analysis of closed-loop data for diagnosing the causes of poor control-loop performance. The main contributions of this work are to utilize HOS tools such as cumulants, bispectrum and bicoherence to develop two new indices: the non-Gaussianity index (NGI) and the nonlinearity index (NLI) for detecting and quantifying non-Gaussianity and nonlinearity that may be present in regulated systems, and to use routine operating data to diagnose the source of nonlinearity. The new indices together with some graphical plots have been found to be useful in diagnosing the causes of poor performance of control loops. Successful applications of the proposed method are demonstrated on simulated as well as industrial data. This study clearly shows that HOS-based methods are promising for closed-loop performance monitoring.