In this book, Higher Order Statistical (HOS) theory is used to develop indices for detecting and quantifying signal non-Gaussianity and nonlinearity. These indices, together with specific patterns in the mapping of process output and controller output are used to diagnose the causes of poor control loop performance.

"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. TOC:Introduction.- Higher Order Statistics: Preliminaries.- Bispectrum and Bicoherence.- Impact of Data Compression and Quantization on Data Driven Process Analyses.- Measures of Nonlinearity - A Review.- Linear or Nonlinear? A Bicoherence Based Measure of Nonlinearity.- A Nonlinearity Measure Based on Surrogate Data Anaylysis.- Nonlinearities in Control Loops.- Diagnosis of Poor Control Performance.- Different Types of Faults in Control Valves.- Stiction: Definition and Discussions.- Physics Based Model of Control Valve Stiction.- Data Driven Model of Valve Stiction.- Describing Function Analysis.- Automatic Detection and Quantification of Valve Stiction.- Industrial Applications of the Stiction Quantification Algorithm.- Confirming Valve Stiction.- Detection of Plantwide Oscillations.- Diagnosis of Plantwide Oscillations.- References."

Higher-Order Statistics.- Higher-Order Statistics: Preliminaries.- Bispectrum and Bicoherence.- Data Quality - Compression and Quantization.- Impact of Data Compression and Quantization on Data-Driven Process Analyses.- Nonlinearity and Control Performance.- Measures of Nonlinearity - A Review.- Linear or Nonlinear? A Bicoherence-Based Measure of Nonlinearity.- A Nonlinearity Measure Based on Surrogate Data Analysis.- Nonlinearities in Control Loops.- Diagnosis of Poor Control Performance.- Control Valve Stiction~- Definition, Modelling, Detection and Quantification.- Different Types of Faults in Control Valves.- Stiction: Definition and Discussions.- Physics-Based Model of Control Valve Stiction.- Data-Driven Model of Valve Stiction.- Describing Function Analysis.- Automatic Detection and Quantification of Valve Stiction.- Industrial Applications of the Stiction Quantification Algorithm.- Confirming Valve Stiction.- Plant-wide Oscillations - Detection and Diagnosis.- Detection of Plantwide Oscillations.- Diagnosis of Plant-wide Oscillations.