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Chapter 5. Simultaneous Design and Control Optimization of PSA Systems Under Uncertainty Since the large-scale PSA model developed is not directly suitable for model based controller design, a system identification step [152, 89, 88, 182] is per- formed to identify a much simpler, preferably linear model relating the control variable with the manipulative variable to reasonable accuracy. The identifica- tion procedure followed in this study involves conducting dynamic simulations on the PDAE model, perturbed by a random pulse of input (feed step duration) disturbance, to ensure that the PSA system is excited persistently [152, 88] over a large frequency band (of interest), in the open loop environment. The result- ing input-output response data (Figure 5.7) is used within the MATLAB system identification toolbox to identify the best fit linear parametric model. The best fit is achieved for a 5th order state space model (Eq. 5.16 to 5.19) with a mismatch of less than 5 % from the PDAE model response. x(k + 1) = Ax(k) + bu(k) y(k) = cx(k) 0.99880 0.10001 0.00169 −0.00164 −0.00034 0.03544 (5.16) (5.17) −0.03130 A= 0.13610 0.96193 −0.18581 −0.04382 0.13967 0.03722 0.13908 0.75535 0.04925 −0.01173 −0.36065 0.79947 0.49361 0.06341 −0.08066 −0.29210 −0.36313 0.02829 133PDF Image | Operation and Control of Pressure Swing Adsorption Systems
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