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Chapter 5. Simultaneous Design and Control Optimization of PSA Systems Under Uncertainty Table 5.6: Modeling parameters for the gas-solid system Parameter KLDFH2 εb Pprod Cpw dp of purity, defined tfeed(k) e(k) tl ∆tl Value Parameter 15×8.89×10−2 KLDFCH4 0.4 εp 7×105 Pbldn 480 ρw 3 T0 Value 15 × 3.96 × 10−3 0.566 101325 7900 303.15 f eed in Eq. 5.11, is treated as the controller performance indicator. = tfeed(k − 1) + Kc(e(k) − e(k − 1)) + Kc∆ts e(k) τI = (P urityH2 (k) − 99.99) × 105 ≤ tfeed(k) ≤ th ≤ ∆tfeed(k) ≤ ∆th (5.10) (5.11) ISE(t) = 105 ∫t 0 (P urityH2 (t) − 99.99)2dt 5.2.3 CSS Definition And Time Horizon of Dynamic Op- timization Problem In an ideal situation, the time horizon should be set to a large value to allow the PSA system to attain a CSS, which is defined as a state in time where all PSA variables take the same value at the start and the end of a cycle. On the other hand, it is well known that most significant changes in process variables usually occur in the few initial cycles. The number of such cycles however, depends upon the PSA design configuration, its operational policy and the gas-solid system. 113PDF Image | Operation and Control of Pressure Swing Adsorption Systems
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