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

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W. A. Fach,H. Heuberger,H.-J. Beckerting a large number of control valves more or less suffering from stiction in chemical or other plants, containing hundreds or thousands control loops. This helps reduce the plant maintenance cost and increase the overall profitability of the plant. A unique feature of the proposed technique is also
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Assessment Based on Minimum-Variance Principles 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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Advanced Control Performance Assessment of the MV benchmark is the approach of generalised MV (GMV) benchmarking, minimising a weighted sum of the control error and control effort. More general but rigorous extensions are the linear-quadratic Gaussian (LQG) benchmark and the model-predictive control (MPC) assessment. These benchmarks are
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Deterministic Controller Assessmentther than stochastic. In these cases, the processes are operated with frequent changes in the references and hence output levels. So, for such systems, deterministic assessment techniques are needed. This chapter presents three methods for control performance assessment based on deterministic criter
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Selection of Key Factors and Parameters in Assessment Algorithmsacy and acceptability of the results of assessment exercises. A fundamental basis for performance assessment is to record and carefully inspect suitable closed-loop data. Pre-processing operations, which are suggested and those which should be strictly avoided, are given in this chapter. The first d
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