Get Advanced control of chemical processes (ADCHEM '94) : IFAC PDF

By D Bonvin; International Federation of Automatic Control

ISBN-10: 0080422292

ISBN-13: 9780080422299

This e-book brings jointly the newest study findings within the key sector of chemical method regulate; together with dynamic modelling and simulation - modelling and version validation for software in linear and nonlinear model-based keep an eye on: nonlinear model-based predictive keep watch over and optimization - to facilitate restricted real-time optimization of chemical tactics; statistical keep an eye on techniques - significant advancements within the statistical interpretation of measured info to steer destiny examine; knowledge-based v model-based control - the mixing of theoretical features of keep an eye on and optimization concept with newer advancements in synthetic intelligence and desktop technology.

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Extra resources for Advanced control of chemical processes (ADCHEM '94) : IFAC symposium, Kyoto, Japan, 25-27 May 1994

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Key Words. Integral Transforms; Modelling ; Parameter Estimation ; System Identification; Waveform Analysis; Wavelets; Poisson Transform kernel in Equation (2) , as 1 . INTRODUCTION t 2'. 0 t < 0 The wavelet transform is a relatively new tech­ nique for multi-resolution analysis. The analy­ sis is accomplished by representing a signal on various scales and resolutions. We introduce a wavelet transform based on the Poisson trans­ form given by f n (/J) = 100 Pn (r, /])f(r)dr (3) where This defines a family of wavelets labelled by the discrete index n € { 1 , 2, 3 , · · · } .

Solid line three-tank system, dashed line = PWT do­ main least-squares fit with no noise. Figure 3: The least-squares fits to noisy data. = Solid line = three-tank system, dots = sample values for three-tank system with noise, dashed line = time domain least-squares fit, dash dot line = Y WT domain least-squares fi t . l shift ponmeter < 7 Figure 4 : Estimated td vs T . Top line is the noise-free case, bottom line is the noise case. x and o mark the best least-squares estimate. Figure 7 : (W1/W2) for FOPDT model with the best PWT n oise-free least-squares fit parame­ ters.

047 I 8 The applica�on of closed-loop simulation is presented in terms of optimal start-up of the process (Figure 4) and in terms of �losed-loop simulation for the tank mixer alone. le 4_ gives the details of the optimal control problem whlle Figures 5a and 5b show the simulated behaviour . (predicted bottom p�od �ct flowrate and composition of . MTBE from the dist1llauon column). OP responses for x2 (out) with a PI-controller and a pred1ct1v� cont�oller. These closed-loop behaviour h �ve been predicted with the linearized model and for the nuxer, the controllability analysis showed that the model can be used for control purposes.

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Advanced control of chemical processes (ADCHEM '94) : IFAC symposium, Kyoto, Japan, 25-27 May 1994 by D Bonvin; International Federation of Automatic Control

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