Armando B. Corripio

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This paper presents the dynamic neural networks partial least squares (DNNPLS) as a strategy for open-loop identification of multivariable chemical processes that circumvent some of the difficulties associated with multivariable process control. The DNNPLS is an extension of the neural networks’ partial least squares (NNPLS) developed by Qin and McAvoy(More)
The objective of this paper is to present what is at least the authors' general assessment of the state-of-the-art of modeling and simulation in the process industries, which in this context is taken to include the chemical, petrochemical, pulp and paper, metals, waste and water treatment industries but excluding the manufacturing industries such as the(More)
A model of a distillation column is developed that includes component and enthalpy balances, equilibrium relationships, variable pressure and complex tray hydraulic relationships. The model is incorporated into a computer program that produces Bode plots of the transfer functions between any input variable and any column variable. The paper includes(More)
The objective of this paper is to present what is at least the authors' general assessment of the state-of-the-art of modeling and simulation in the process industries, which in this context is taken to include the chemical, petrochemical, pulp and paper, metals, waste and water treatment industries but excluding the manufacturing industries such as the(More)
A tunable feedback control algorithm is developed for a first-order plus dead time process which has a variable sample interval and a variable dead time. This variable sample interval, variable dead time (VSIVDT) controller is applied to controlling the product composition of a blender using off-line composition analysis. The blender and controllers are(More)
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