Robust and Asymmetric Assessment of the Benefits from Improved Control – Industrial Validation

Domański, Paweł D.; Golonka, Sebastian; Marusak, Piotr M.; Moszowski, Bartosz

doi:10.1016/j.ifacol.2018.09.260

Cited by 8 publications

(3 citation statements)

References 12 publications

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“…• integral time measures, e.g., Mean Square Error (MSE), Integral Absolute Error (IAE) [86], Integral Time Absolute Value (ITAE) [87], Integral of Square Time derivative of the Control input (ISTC) [88], Total Squared Variation (TSV) [89], and Amplitude Index (AMP) [71]; • correlation measures, such as oscillation detection index [90] or relative damping index [91]; • statistical factors utilizing different probabilistic distribution function (standard deviation, variance, skewness, kurtosis, scale, shape, etc.) [92], variance band index [93], or the factors of other probabilistic distributions [94][95][96]; • benchmarking methods [97]; and • alternative indexes using wavelets [98], orthogonal Laguerre [99] and other functions [65], Hurst exponent [100], persistence measures [101,102], entropy [103][104][105], multifractal approaches [106], or fractional-order [107,108].…”

Section: Data-driven Methodsmentioning

confidence: 99%

Performance Assessment of Predictive Control—A Survey

Domański

2020

Algorithms

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Model Predictive Control constitutes an important element of any modern control system. There is growing interest in this technology. More and more advanced predictive structures have been implemented. The first applications were in chemical engineering, and now Model Predictive Control can be found in almost all kinds of applications, from the process industry to embedded control systems or for autonomous objects. Currently, each implementation of a control system requires strict financial justification. Application engineers need tools to measure and quantify the quality of the control and the potential for improvement that may be achieved by retrofitting control systems. Furthermore, a successful implementation of predictive control must conform to prior estimations not only during commissioning, but also during regular daily operations. The system must sustain the quality of control performance. The assessment of Model Predictive Control requires a suitable, often specific, methodology and comparative indicators. These demands establish the rationale of this survey. Therefore, the paper collects and summarizes control performance assessment methods specifically designed for and utilized in predictive control. These observations present the picture of the assessment technology. Further generalization leads to the formulation of a control assessment procedure to support control application engineers.

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Section: Data-driven Methodsmentioning

confidence: 99%

Performance Assessment of Predictive Control—A Survey

Domański

2020

Algorithms

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“…Although the same limit approach possesses some deficiencies and constraints, like not evident distributions, it is frequently used in practice [14].…”

Section: Predicting Economic Benefits Of Control Improvementsmentioning

confidence: 99%

Multicriteria Ammonia Plant Assessment for the Advanced Process Control Implementation

et al. 2020

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Rehabilitation of control systems or implementation of Advanced Process Control (APC) in any large scale industrial installation poses several challenges. First of all, the implementation process has to meet stringent safety regulations. Moreover, it has to minimize normal production violation. All human, technology and control system risks need to be identified and a mitigation plan has to be prepared. Once the implementation limitations are fulfilled the installation requires to be prepared. The plant needs to be comprehensively assessed. All APC project related aspects, like control system or process instrumentation must be reviewed. Furthermore existing installation performance has to be measured for further justification of project results. The paper presents authorial assessment methodology aiming at the installation preparation before APC implementation. It is obvious that any supervisory control helps only when the underlying process, infrastructure and regulatory base control operates properly. Any performance malfunctioning within plant equipment or base control logic misfit limits, even the most sophisticated APC. The paper presents developed and practically adopted comprehensive multicriteria assessment procedure, which prepares the large scale chemical installation for APC supervisory control upgrade. Proposed procedure is accompanied with identified implementation risks and their mitigation plan.INDEX TERMS APC, ammonia plant, control system quality, equipment assessment, multicriteria analysis.

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“…Asymmetrical fault correction has been addressed in [12]. An asymmetric approach to the estimation of the benefit resulting from the improved control has been analyzed in [13]. Despite the above examples, asymmetry is rather infrequent in control engineering research.…”

Section: Introductionmentioning

confidence: 99%

Control Quality Assessment for Processes With Asymmetric Properties and its Application to pH Reactor

Domański

Ławryńczuk

2020

IEEE Access

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The majority of processes in chemical industry is nonlinear. However we often take advantage of linear approximation and analysis as the useful simplification. Nonetheless, one has to remember that the reality is often complex, nonlinear and full of unknown unknowns. One of the forgotten aspects in control engineering is connected with the symmetricity. Asymmetric properties appear, when the process or instrumentation introduces nonlinearities. Control systems are then exposed to the asymmetrical behavior and should properly react, while their performance measures have to take them into account. This paper proposes robust control performance indexes in form of the M-estimator using logistic ψ function denoted σ H and α-stable distribution scale factor γ. Additionally, their application procedure in industrial chemical engineering environment is proposed. The approach is illustrated with an example of the pH neutralization process. INDEX TERMS Asymmetry, control performance assessment, fat-tails, MPC, pH neutralization.

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Robust and Asymmetric Assessment of the Benefits from Improved Control – Industrial Validation

Cited by 8 publications

References 12 publications

Performance Assessment of Predictive Control—A Survey

Performance Assessment of Predictive Control—A Survey

Multicriteria Ammonia Plant Assessment for the Advanced Process Control Implementation

Control Quality Assessment for Processes With Asymmetric Properties and its Application to pH Reactor

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