Analysis of multivariable control performance assessment techniques

Yuan, Qiaolin; Lennox, Barry; McEwan, Matthew

doi:10.1016/j.jprocont.2008.10.001

Cited by 25 publications

(12 citation statements)

References 21 publications

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“…Another variance‐based index also proposed in the literature corresponds to the trace of the covariance matrix (η, see bellow), i.e. the sum of variances of each output under control Using matrix algebra, this index can also be re‐written as However, this index completely ignores all the off‐diagonal elements of the covariance matrices, being only adequate when the output variables are approximately independent19, 21, which is not a common situation, especially in current highly interactive industrial processes. The volume‐like index, on the other hand, is able to take into account all the covariance information and interactions between output variables, in case they exist.…”

Section: Methodsmentioning

confidence: 99%

“…Model structure selection can be guided by some rules and analytical procedures, but, in the end, there are usually a set of candidate models to be considered, and the decision is not always a trivial one. Furthermore, quite often, the lower bond estimated is not even effectively attainable for a large variety of systems (neither is that desirable18, 19), and the degree to which it can be approached varies from system to system, which renders the analysis of these benchmarks circumstantial, as happens for the historical‐data benchmarks.…”

Section: Methodsmentioning

confidence: 99%

“…Both the model‐based and data‐driven approaches to CPA/CPM referred so far are based on the variance of the outputs and, despite the difference in the methodologies adopted, all of them are known as ‘variance‐based’ CPA/CPM approaches19. Other class of methodologies have also been developed and proposed in the literature, which use different measures, such as, for instance, the adoption of classical dynamical features characterizing the response of a system under control to deterministic and known perturbations (rise time, settling time, overshoot, stationary off‐set, etc 13…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Statistical monitoring of control loops performance: an improved historical‐data benchmark index

Rato

Reis

2010

Quality & Reliability Eng

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Control systems are key elements of virtually all industrial processes, whose performance directly impacts aspects as important as: product quality and variability, operations safety, process efficiency/costs and environmental impact. In this paper we address the problem of monitoring the performance of such control systems, and in particular a new historical-data benchmark index is proposed (I M ), which is able to discern between perturbations in the system's core modules, which are under the supervision of process owners, from those originated at the level of disturbances, usually involving other stakeholders. It is a generalization of the current index (I v ) as it can be shown that it reduces to this index for the particular case where the variability of the disturbances is the same as in the reference or benchmark period and in the monitoring period. The results obtained demonstrate that the proposed historicaldata benchmark index is able to maintain the target false alarm rate under situations where the variability of the disturbances increases, a situation where the current index, I v , fails. When the disturbances variability is maintained, both indices present similar detection capability, as expected. The subsequent identification of the modules in fault was also analysed, and the results show that the proposed methodology is able to identify the general source of the degradation in the controller performance, namely, if it is due to a perturbation within the system's core (and which loop is affected) or at the level of the disturbances (increasing variability of the loads or change in their dynamical behaviour).

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Statistical monitoring of control loops performance: an improved historical‐data benchmark index

Rato

Reis

2010

Quality & Reliability Eng

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“…Experience has shown that companies do their best when they focus their process-improvement efforts on a manageable number of process areas or those business decisions that require increasingly sophisticated effort as the organization improves (Ladley 2010;Yuan et al 2009;Zinkevičiūtė 2007;Humphrey 1989). A maturity level is a defined evolutionary scale of process improvement.…”

Section: Organization Process Maturity: a Review Of The Literaturementioning

confidence: 99%

Managing Maturity in Process-Based Improvement Organizations: A Perspective of the Romanian Companies

Pãunescu

Acatrinei

2012

Journal of Business Economics and Management

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Building upon various models from the literature which assess the maturity level achieved by an organization at one moment in time, the paper introduces a model which helps organizations, interested in remaining competitive and achieving sustainability, to monitor and evaluate their process performance. Such as, the paper analyzes the relationships that exist among the critical components of an organization's management system at the strategic and operational level so that key drivers will become the heart of sustainable development. In particular, the paper focuses on how the organizational system influences process maturity profile of the Romanian companies. Data were collected in face-to-face structured-questionnaire interviews from 1302 public and private organizations from Romania. The dearth of empirical research examining organization process maturity in emerging countries constitutes a critical gap in the business process management literature that needs much more attention from scholars. For the purpose of this paper, a factor analysis was employed to explain the pattern of correlations within a set of observed variables that determine the process maturity profile of the Romanian companies. The research results show that there are strong positive correlations between the variables examined that account for a higher level of maturity and performance of organization's processes.

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“…Moreover, an overview of CPA was published in a special issue of the International Journal of Adaptive Control and Signal Processing [26]. Generally, CPA approaches can be classified into the following benchmarkings: MVC benchmarking, linear quadratic Gaussian benchmarking, MPC benchmarking, user specified benchmarking and historical data benchmarking [27]. Among these methods, prediction error approach is one of the most promising ones which does not need the interactor matrix.…”

Section: Control Performance Assessmentmentioning

confidence: 99%

Performance assessment of cascade controllers for nitrate control in a wastewater treatment process

Liu

2011

Korean J. Chem. Eng.

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A cascade control strategy is proposed to the benchmark simulation model 1 (BSM1) to enhance the treatment performance of nitrogen removal in a biological wastewater treatment plant. The proposed control approach consists of two control loops, a primary outer loop and a secondary inner loop. The method has two controllers of which the primary loop has a model predictive control (MPC) controller and the secondary loop has a proportional-integralderivative (PID) controller, which is a cascade MPC-PID controller. The primary MPC controller is to control the nitrate concentration in the effluent, and the secondary PID controller is to control the nitrate concentration in the final anoxic compartment. The proposed method controls the nitrate concentrations in the effluent as well as in the final anoxic reactor simultaneously to strictly satisfy the quality of the effluent as well as to remove the effects of disturbances more quickly by manipulating the external carbon dosage rate. Because the control performance assessment (CPA) technique has the features of determining the capability of the current controller and locating the best achievable performance, the other novelty of this paper is to suggest a relative closed-loop potential index (RCPI) which updates the CPA technology into a closed-loop cascade controller. The proposed method is compared with a cascade PID-PID control strategy and the original PID controller in BSM1 and an improved performance of the suggested cascade MPC-PID controller is obtained by using the CPA approach.

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Analysis of multivariable control performance assessment techniques

Cited by 25 publications

References 21 publications

Statistical monitoring of control loops performance: an improved historical‐data benchmark index

Statistical monitoring of control loops performance: an improved historical‐data benchmark index

Managing Maturity in Process-Based Improvement Organizations: A Perspective of the Romanian Companies

Performance assessment of cascade controllers for nitrate control in a wastewater treatment process

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