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Chapter 4. Explicit/Multi-Parametric MPC Control of PSA Systems Figure 4.1: The receding horizon policy employed in the MPC implementation min Z = u s.t. x(t + ∆t) = y(t) = ulow ≤ u(t) ∆ulow ≤ ∆u(t) ylow ≤ y(t) (y(t) − yr(t))′(y(t) − yr(t)) + ∆u(t)′R∆u(t) t=0 Hp−1 H −1 u ∑∑ t=1 Ax(t) + bu(t) cx(t) ≤ uhigh ≤ ∆uhigh ≤ yhigh (4.1) The actual functioning of MPC is based on the receding horizon philosophy (see also Figure 4.1), where the current plant state and output variables, along with a suitable plant model, are utilized to calculate the future sequence of op- timal input variables. The following main steps are involved in calculating the optimal control move. Step 1 At time t, the plant output variables (y) are measured and are employed to obtain the latest estimate of the state variables (x). 60PDF Image | Operation and Control of Pressure Swing Adsorption Systems
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