Titlebook: Control Performance Management in Industrial Automation; Assessment, Diagnosi Mohieddine Jelali Book 2013 Springer-Verlag London 2013 Contr

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Statistical Process Controllone; it is an umbrella term for the set of activities and methods for data analysis and quality control. This chapter contains a brief description of selected univariate and multivariate SPC techniques.

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Detection of Loop Nonlinearitiesrence property led to the bicoherence technique. Alternatively, the surrogate analysis method, which is based on the regularity of phase patterns in nonlinear time series, can be used. Both methods are presented in this chapter, and a comparative study is given on some industrial data sets.

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Conscientious

Industrial CPM Technology and Applicationsontrol performance auditing or monitoring. The primary purpose of this chapter is to present an overview of CPM industrial applications and (available) software products. A comprehensive overview of published CPM applications to industrial processes and commercially available CPM products are given.

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Indigence

Performance Monitoring and Improvement Strategiesategies for monitoring the performance of complex process-control systems are introduced. A comprehensive control-performance assessment procedure is proposed combining different methods described throughout the previous chapters of the book.

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Von CIM zur Unternehmensintegration MV benchmark (as a reference performance bound) can be estimated from routine operating data without additional experiments, provided that the system delay is known or can be estimated with sufficient accuracy. The main focus of the chapter is on presenting assessment methods based on minimum-varia

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Von CIM zur Unternehmensintegrationractice, however, there are many other limitations on the achievable control performance, such as constraints on controller order, structure, and action. Many researchers have introduced modified/extended versions of the Harris index to include design specifications of the user (such as the rise tim

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