Sequential Control Performance Diagnosis of Steel Processes

Recalde, Luis F.; Katebi, Reza; Yue, Hong

doi:10.3182/20140824-6-za-1003.00557

Cited by 1 publication

(1 citation statement)

References 18 publications

(21 reference statements)

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“…Real oxyfuel furnace data provided by Swerea MEFOS (One of the partners of the Cognitive Control Project completed in our previous work (Recalde, Katebi, and Tauro, 2013;Recalde, Katebi, and Yue, 2014) was employed in this CPM study. The furnace is used to reheat the slabs coming from the rolling mill and consists of 2 parts being The temperature setpoints (T sp ) for these zones are also added for illustration and comparison.…”

Section: Cpm Wiht Real Oxyfuel Furnace Datamentioning

confidence: 99%

Control Performance Monitoring of State-Dependent Nonlinear Processes

Recalde

Yue

2017

IFAC-PapersOnLine

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This paper presents a novel approach to monitor control performance of nonlinear processes that can be described as state-dependent models (SDMs). A discrete Kalman filter (KF) is established to estimate the SDM parameters. A covariance control formulation is introduced to split the system closed-loop variance/covariance into two terms, one term to account for the minimum expected quadratic loss bound (equivalent to the minimum variance performance bound but in state space formulation), and another to account for performance deviations from the minimum variance bound. Simulation studies have been conducted on several nonlinear process systems including a cold rolling mill model with roll eccentricity and a steel making system with real time oxyfuel slab reheating furnace control data. The case study results demonstrate the computational efficiency of the proposed strategy in real time monitoring and control of systems with fast, nonlinear and time-varying dynamics.

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Section: Cpm Wiht Real Oxyfuel Furnace Datamentioning

confidence: 99%