Model assessment of MPCs with control ranges: An industrial application in a delayed coking unit. (March 2019)

• Record Type: Journal Article
• Authors: Botelho, Viviane Rodrigues; Trierweiler, Jorge Otávio; Farenzena, Marcelo; Longhi, Luis Gustavo S.; Zanin, Antônio Carlos; Teixeira, Herbert Campos G.; Duraiski, Ricardo Guilherme
• Is Part Of: Control engineering practice. Volume 84(2019)
• Page Start: 261
• Page End: 273
• Publication Date: 2019-03
• Subjects: Model predictive control -- Model assessment -- Model-plant mismatch -- Unmeasured disturbance -- Control ranges; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2018.11.003
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: Poor model quality is one of the most frequent causes of performance deterioration in Model Predictive Controllers. As such, frequent model evaluation and correction is fundamental. Some assessment methods are reported in the literature, but most cannot deal with Model Predictive Controllers (MPCs) without fixed setpoints for controlled variables. Botelho et al. (2015, 2016a, 2016b) proposed a series of methods that include the controller tuning and the applied MPC implementation in the assessment procedure. Their main advantage is setpoint independence. This paper analyzes the application of these methods in an industrial MPC with control ranges. The system studied is an MPC of a fractionating column in a delayed coker unit of a refinery in Brazil. The results demonstrate that the method is capable of correctly quantifying the effect of modeling problems and identifying whether they are related to a model-plant mismatch or unmeasured disturbance. Highlights: The model assessment of a real industrial application of MPC in a delayed coker unit is shown. The evaluated MPC is characterized by operating in control ranges. The methods proposed by Botelho et al. (2015, 2016a, 2016b) are used for the modeling errors quantification. The most important modeling problems are pointed by the method.