This paper presents a Bayesian approach, based on infinite Gaussian mixtures, for the calculation of control limits for a multivariate statistical processcontrol scheme. Traditional approaches to calculating control ...
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A batch-to-batch iterative product quality optimisation control strategy for a batch polymerisation reactor is proposed. Recurrent neural networks are used to model the dynamic behaviour of product quality variables. ...
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In the present work, the matrix notation is used to derive the IMC decentralized and centralized PI controllers. Maclaurin series is applied to the resulting equation to get the controller parameters. For design of th...
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Successful application of model based control depends on having good estimates for the system dynamic states and parameters. A multivariate dynamic linear model is developed for the estimation of the states from limit...
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This paper presents an integrated batch-to-batch control and within batch re-optimisation control strategy for batch processes using neural network models. To overcome the difficulties in developing detailed mechanist...
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Partial Least Squares (PLS) is a popular method for the development of a framework for the detection and location of process deviations. A limitation of the approach is that it has generally been used to monitor one r...
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This paper proposes the application of Gaussian process regression for the empirical modelling of batch processes to provide long range predictions. Gaussian processes are flexible, non-parametric Bayesian regression ...
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Fault detection and diagnosis are important for the safe and efficient operation of a chemical plant. This paper proposes a weighted combined contribution plot. Fault identification using either Q or T2 contribution p...
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The performance of a control chart in statistical processcontrol is often quantified in terms of the Average Run Length (ARL). The ARL enables a comparison to be undertaken between various monitoring strategies. Thes...
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Calibration-free resolution techniques provide an alternative approach to the development of a calibration model. These combine spectroscopic measurement coupled with mathematical and statistical assumptions and give ...
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