New PDF release: Advanced control of chemical processes (ADCHEM '94) : IFAC
By D Bonvin; International Federation of Automatic Control
This booklet brings jointly the newest learn findings within the key sector of chemical procedure keep watch over; together with dynamic modelling and simulation - modelling and version validation for software in linear and nonlinear model-based keep watch over: nonlinear model-based predictive regulate and optimization - to facilitate limited real-time optimization of chemical techniques; statistical keep an eye on techniques - significant advancements within the statistical interpretation of measured info to lead destiny learn; knowledge-based v model-based control - the combination of theoretical features of keep watch over and optimization thought with more moderen advancements in synthetic intelligence and laptop technology.
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Additional resources for Advanced control of chemical processes (ADCHEM '94) : IFAC symposium, Kyoto, Japan, 25-27 May 1994
Another random step sequence (not shown, but different from the one used for the identification) is used to validate the iden tified models. The model responses to this validation sequence are shown in Figure 3, where the solid line represents the "true" process response. Observe that the reactor output predicted by the different models match the "true" output very well. Relative prediction error variances are shown in Table 2 below for both the 3-parameter model and the 6-parameter model. Observe that unlike the first example, this polymer reactor model is not of the form in (3).
Comput. Chem. , 17(S), S263-S283. , B. S. Bossen, R. Gani (1992), Steady state and dynamic simulation of complex chemical processes. Chem. Eng. Res. , 70, 99-109. Perregaard, J. , Comput. Chem. , 17(5/6), 465-484. S0rensen, E. L ( 1991), Dynamic simulation of chemical processes with accurate thermodynamic models. D. Thesis, The Technical University of Denmark, September, 1991. Figure 6 : Comparison of predicted closed-loop response for x2 out from mixer. Dashed line is Pl-controller and continuous line is predictive controller.
6 ·. 0-'' ... 4 0 . 10 5 15 20 2' time [hr) 30 0-' 40 35 45 50 Fig. 2. 5033 0. ta set, we investigate first the situation in which the parameters >0 , ¢>1 , ;2 are pre-specified to be zero, and only the non-zero parameters are identified . The es timates returned for these parameters by the three identification schemes are summarized in Table 1 be low:( idct refers to the continuous time least squares method; dint refers to the direct integration method; and vint refers to the "velocity" form).
Advanced control of chemical processes (ADCHEM '94) : IFAC symposium, Kyoto, Japan, 25-27 May 1994 by D Bonvin; International Federation of Automatic Control