By International Federation of Automatic Control, Heinz Unbehauen
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Extra info for Adaptive Control of Chemical Processes 1985
Relative to the objective *> quantity selected fuel gas 1. naphta t—^cracking tube 7 [■ OJ = constant of proportionality. The membership functions for the naphta mixture class 1 are shown in Pig·2. 3. [ | I—i\cracking tube 2 f I t—+\ cracking tube 3 \ vapour 4. Solution of the optimization task (3) subject to the constraints (1), (2), (4), (5), (6) for each class representative of the naphta mixtures. As an optimization method the Bellmanian dynamic programming has been used. 4 the optimal control for the naphta mixture class 1 is presented.
Another problem with this multiloop configuration is how to adjust the controllers when the parameters of the system change. The general aproach is tuning the controllers to get an acceptable overall response at a certain operating condition and yet have a good stability margin to account for possible variations in the system parameters. A basic requirement for obtaining a robust controller is the selection of a suitable model structure, able to give an adequate description of the system within the desired operating range.
From such a representation, a suitable combination of measurement set, sampling interval and model structure can be selected. J0rgensen et al. (1985) have described a method to systematize the procedure described above into essentially three steps, based upon the purpose of the control design: heat capacity of the pellets and the capacity of heat transport of the flowing gas. Figure 1 shows the internal coupling through the chemical reaction between the enthalpy and the oxygen, and from the total mass to the other two quantities.