Performance assessment of MIMO systems based on I/O delay information

Xia, Hao; Majecki, Paweł; Ordys, Andrzej; Grimble, M.J.

doi:10.1016/j.jprocont.2005.06.017

Cited by 29 publications

(27 citation statements)

References 12 publications

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“…For the described system, the MV index has been calculated for various values of d . 15 In this study, the system is simulated with different values of d , and the data of system outputs are measured for each case. Next, the Hurst exponents of system outputs are calculated with DFA and RRA methods using the stored data from simulations.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Further research was performed to extend the MV index for MIMO systems. [10][11][12][13][14][15][16][17] In MIMO systems, the interaction between control loops should also be considered. As a result, due to the interactions between different variables, the required prior information and the computational burden to obtain the MV index are increased.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Data-driven performance assessment of multivariable control loops using a modified Hurst exponent–based index

Khosroshahi

Poshtan

2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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Control system performance assessment is significant, especially in practical applications. One of the most important indices for the performance assessment of control systems is minimum variance. Calculating the minimum variance index in multivariate systems requires prior knowledge of system parameters and models, and is therefore an obstacle in practical applications. In this article, an index is proposed for the performance assessment of multivariate control loops, evaluating the system performance with the minimum variance criterion and using only the system’s routine operation data. This index can quantify the performance using neither any prior knowledge of system parameters nor the system’s optimal operation data. The proposed index is based on the Hurst exponent, a parameter for measuring correlations in time series data. In this article, detrended fluctuation analysis and rescaled range analysis are used to estimate the Hurst exponents of system outputs. Using a combination of these Hurst exponents, an index is defined for the performance assessment of multivariate systems. The results of simulation examples illustrate that the proposed index can assess the performance efficiently.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Data-driven performance assessment of multivariable control loops using a modified Hurst exponent–based index

Khosroshahi

Poshtan

2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…The absence of a symptom does not guarantee that it is fully operational. Monitoring control loop performance approaches are also used to detect degradation in the functioning of control loops [Harris, 1989;Xia et al, 2006, Saha P et al, 2012.…”

Section: Towards a Unified Approach To Detection Of Faults And Cyber-...mentioning

confidence: 99%

Towards a unified approach to detection of faults and cyber-attacks in industrial installations

Kościelny

Syfert

Ordys

et al. 2021

2021 European Control Conference (ECC)

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This paper investigates enhancing the ability to detect cyber-attacks by using information and methods related to fault detection. An experimental stand, and an associated simulator have been constructed to enable tests of combined cyber attacks and faults in industrial processes, and, possibly, to distinguish between them. Some scenarios of cyber attacks have been presented, analysed theoretically and then tested on the simulator, demonstrating that detection of cyber attacks by this method is possible.

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“…This performance benchmark is defined as the ratio of the trace of the current closed-loop system output covariance matrix and that obtained under the multivariate MV benchmark. 24 Such index ignores the correlation between control loops. Therefore, it is not sufficient for monitoring the performance of MIMO systems.…”

Section: Introductionmentioning

confidence: 99%

Online performance monitoring and diagnosis of multivariate systems

Moghbeli

Poshtan

2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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Online performance monitoring can be used to improve the performance of control systems in industry. The purpose of this article is to detect a performance deterioration and determine its cause in a system. In this article, two indices are used for online performance monitoring of a nonlinear multivariate system with optimally tuned proportional integral controllers. The first index is defined based on a squared distance measurement between the closed-loop system outputs and chosen set-points. The second index is a statistical index that uses all the information in the covariance matrices of the closed-loop system output data. Both indices are used and compared for performance monitoring of a quadruple-tank system. Moreover, hypothesis testing method has been used to determine the cause of the performance deterioration, so that appropriate solutions according to the cause can be applied to the system to improve the performance.

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Performance assessment of MIMO systems based on I/O delay information

Cited by 29 publications

References 12 publications

Data-driven performance assessment of multivariable control loops using a modified Hurst exponent–based index

Data-driven performance assessment of multivariable control loops using a modified Hurst exponent–based index

Towards a unified approach to detection of faults and cyber-attacks in industrial installations

Online performance monitoring and diagnosis of multivariate systems

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