Estimation of cross‐directional properties: Scanning vs. Stationary Sensors

Tyler, Matthew L.; Morari, Manfred

doi:10.1002/aic.690410412

Cited by 27 publications

(21 citation statements)

References 10 publications

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“…We also define an effectiveness factor , similar to the one used in [18], to measure the closed-loop control benefit original estimator tuning estimator tuning (25)…”

Section: F Quantifying the Control System Performance Benefitsmentioning

confidence: 99%

The autocovariance least-squares method for estimating covariances: application to model-based control of chemical reactors

Odelson¹,

Lutz

Rawlings

2006

IEEE Trans. Contr. Syst. Technol.

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Abstract-This paper demonstrates the autocovariance least-squares (ALS) technique on two chemical reactor control problems. The method uses closed-loop process data to recover the covariances of the disturbances entering the process, which are required for state estimation. The data used for this purpose may be collected with or without the controllers running. We do not assume that the plant is at steady state nor that only nonzero disturbances are affecting the plant at the time of data collection. The ALS method also accounts for integrated white noise disturbances, which are required for offset-free control. Two examples are provided in this paper: a carefully controlled laboratory reactor and an industrial reactor controlled by a state-of-the-art advanced model predictive control (MPC) system. A variety of control scenarios are tested and the results demonstrate that the ALS method has the potential to improve the best industrial practice of process control by a factor of three to five.

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“…We also define an effectiveness factor , similar to the one used in [18], to measure the closed-loop control benefit original estimator tuning estimator tuning (25)…”

Section: F Quantifying the Control System Performance Benefitsmentioning

confidence: 99%

The autocovariance least-squares method for estimating covariances: application to model-based control of chemical reactors

Odelson¹,

Lutz

Rawlings

2006

IEEE Trans. Contr. Syst. Technol.

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“…constant and a time-varying C k is employed. The C k is a vector with an entry 1 corresponding to the current measured Ž state and 0 elsewhere Bergh and MacGregor, 1987;Tyler . and Morari, 1995;Rawlings and Chien, 1996 .…”

Section: Modelingmentioning

confidence: 99%

“…The Kalman filter is the natural choice for the state estimation problem as discussed by several au-Ž thors Bergh and MacGregor, 1987;Chen, 1992;Wang et al, . 1993;Tyler and Morari, 1995;Rawlings and Chien, 1996 . Ž .…”

Section: Introductionmentioning

confidence: 98%

Design sensor trajectory for control: Application to sheet‐forming processes

Chang¹,

Yu²,

Chien³

2000

AIChE Journal

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“…The dynamic bandwidth of the control system could be increased with full web-width measurement arrays. The effect of different measurement scenarios and scanner path arrangements to estimation error are given in (Tyler and Morari, 1995;Chang et al, 2001). Efforts on finding a feasible and cost-effective solution for full web width measurement systems have been made (Francis, 1991;Williams et al, 1996;Ferguson, 1997;Raunio et al, 2010;Söderberg et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

ultiple Property Cross Direction Control of Paper Machines

Ohenoja¹,

Leiviskä²

2011

MIC

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Cross direction (CD) control in sheet-forming process forms a challenging problem with high dimensions. Accounting the interactions between different properties and actuators, the dimensionality increases further and also computational issues arise. We present a multiple property controller feasible to be used especially with imaging measurements that provide high sampling frequency and therefore enable short control interval. The simulation results state the benefits of multiple property CD control over single property control and single property control using full feedforward compensation. The controller presented may also be tuned in automated manner and the results demonstrate the effect of tuning on input saturation.

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Estimation of cross‐directional properties: Scanning vs. Stationary Sensors

Cited by 27 publications

References 10 publications

The autocovariance least-squares method for estimating covariances: application to model-based control of chemical reactors

The autocovariance least-squares method for estimating covariances: application to model-based control of chemical reactors

Design sensor trajectory for control: Application to sheet‐forming processes

ultiple Property Cross Direction Control of Paper Machines

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