The subject matter of the book is concerned with the detection and diagnosis of process nonlinearities from routine process data. In general, processes can be treated as locally linear and measures of overall process performance can be monitored from routine operating data. However when process performance is not satisfactory then it is imperative that the cause of poor performance be diagnosed. Poor performance can be due to several reasons. Statistics abound on the cause of poor control performance. It has been documented that as many as 40% of the control loops in industry perform unsatisfactorily because of valve problems, a majority of them due to valve stiction, causing the closed loop system to become nonlinear. The development of signal processing methods to detect and quantify process nonlinearity from routine process data is the main subject matter of this book.
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