Sensitivity analysis for selective constraint and variability tuning in performance assessment of industrial MPC

Lee, Kwan Ho; Huang, Biao; Tamayo, Edgar C.

doi:10.1016/j.conengprac.2008.01.007

Cited by 30 publications

(21 citation statements)

References 26 publications

(38 reference statements)

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“…The algorithms for MPC economic performance assessment and tuning guidelines have been introduced in [Xu et al, 2007]. Also, this APC performance analysis tool includes a sensitivity analysis, which provides a selective constraint/variability tuning guidelines for benefit improvement in practice [Lee et al, 2007]. In the following, the main concepts for LMIPA will be summarized.…”

Section: Apc Economic Performance Assessmentmentioning

confidence: 99%

“…The problem of finding sensitive or profitable process variables to the economic profit is of prime importance in process control engineering and plant optimization. For a selective constraint/variability tuning guideline, see a sensitivity analysis in Lee et al [2007].…”

Section: Constraint/variablity Tuning For a Desired Yieldmentioning

confidence: 99%

“…To perform sensitivity analysis [Lee et al, 2007] for the case studies and suggest selective tuning guidelines, we calculate the benefit potentials. The ideal and existing benefit potentials are given by ∆J I = 2.369 and ∆J E = 2.369, respectively.…”

Section: Selective Constraint Tuning Guidelinesmentioning

confidence: 99%

“…To find an alternative to achieve the desired benefit potential, the constraint tuning optimization in [Lee et al, 2007] has been solved. From the optimization result, we observe that there is no feasible solution for this case study.…”

Section: Selective Constraint Tuning Guidelinesmentioning

confidence: 99%

“…Case study 2: Maximizing the operating point of CV8 To find the second profitable PV, the constraint tuning optimization in [Lee et al, 2007] has been solved. From the optimization result, we find that the most profitable PV is MV5, which is not a quality variable.…”

Section: Selective Constraint Tuning Guidelinesmentioning

confidence: 99%

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Controller Performance Analysis Technology for Industry: Implementation and Case Studies

Lee

Huang

et al. 2008

IFAC Proceedings Volumes

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In this paper, an industrial MPC performance monitoring technology is introduced with a focus on the industrial implementation. A plant-oriented framework for APC performance monitoring is proposed on the basis of industrial computer control systems background. A software package integrating this technology, which is called Performance Analysis Toolbox and Solutions (PATS), is introduced. The major components of PATS are discussed including process data collection, data preprocessing, process model identification, similarity clustering, control valve stiction detection, multivariate controller performance assessment, and APC economic performance assessment using linear matrix inequality optimization. An industrial case study of a hydrogen unit is illustrated. A limited trial version of the software package can be downloaded from the web

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Section: Apc Economic Performance Assessmentmentioning

confidence: 99%

Section: Constraint/variablity Tuning For a Desired Yieldmentioning

confidence: 99%

Section: Selective Constraint Tuning Guidelinesmentioning

confidence: 99%

Section: Selective Constraint Tuning Guidelinesmentioning

confidence: 99%

Section: Selective Constraint Tuning Guidelinesmentioning

confidence: 99%

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Controller Performance Analysis Technology for Industry: Implementation and Case Studies

Lee

Huang

et al. 2008

IFAC Proceedings Volumes

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On the tuning of predictive controllers: Impact of disturbances, constraints, and feedback structure

Omell

Chmielewski

2014

AIChE Journal

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The impact of problem formulation modifications on predictive controller tuning is investigated. First, the proposed tuning method is shown to adapt to disturbance characteristic changes and thus, takes full economic advantage of the scenario. The second topic concerns point-wise-in-time constraints and the impact of constraint infeasibility. Specifically, we shift the tuning question from selection of nonintuitive weighting matrix parameters to that of a few key parameters and results in a rather intuitive trade-off between expected profit and expected constraint violations. Finally, we show that simple modifications will allow for the consideration of various feedback structures, including computational delay and partial state information. The overall conclusions of the work are that the results of the automated algorithm will help build an intuitive understating of the dynamics of the process and ultimately result in a higher level trade-off between profit and constraint observance.

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Determining the state of a process control system: Current trends and future challenges

Shardt

Zhao

et al. 2011

Can J Chem Eng

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In many industrial plants, multiple, interconnected control loops are common. Their maintenance and improvement requires detailed controller performance assessment to determine not only whether they are behaving well, but also to determine the potential cause of any observed problems. Techniques for performance assessment can be divided into two broad categories (1) performance assessment of regulatory control loops; and (2) performance assessment of supervisory control loops that evaluate the economic performance of advanced control strategies, such as model predictive control (MPC). A comprehensive review of the literature on the industrial applications of performance assessment, as well as some of the currently available software, is also presented. © 2011 Canadian Society for Chemical Engineering

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Sensitivity analysis for selective constraint and variability tuning in performance assessment of industrial MPC

Cited by 30 publications

References 26 publications

Controller Performance Analysis Technology for Industry: Implementation and Case Studies

Controller Performance Analysis Technology for Industry: Implementation and Case Studies

On the tuning of predictive controllers: Impact of disturbances, constraints, and feedback structure

Determining the state of a process control system: Current trends and future challenges

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