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Chapter 4. Explicit/Multi-Parametric MPC Control of PSA Systems Modeling & Simulation System Identification Model Based Control & Validation ‘High Fidelity’ PSA Model ‘Approximate’ Model Multi-Parametric Programming In-silico closed loop controller validation Extraction of explicit MPC controllers u = u(x(θ)) Figure 4.2: Framework for multi-parametric programming and explicit/multi- parametric MPC rived controllers. The high fidelity model built in step 1 now acts as the virtual PSA plant. Closed loop responses of the controllers are obtained for various type of disturbances and mp-MPC tuning parameters. If the controller performance is not satisfactory, the whole process is repeated again, until desired performance is obtained. 4.3 PSA Mathematical Modeling and Simula- tion 4.3.1 PSA Dynamic Model A detailed, first principle based mathematical model of the PSA system is de- veloped for this study in gPROMS (PSE, Ltd.). Figure 4.3 shows a graphical overview of the PSA system under consideration. Each of the four beds contains activated carbon as an adsorbent and undergoes a cyclic operation comprising nine process steps [83], separating a 70% H2 and 30 % CH4 mixture into high purity H2. The main features of the dynamic model are shown here (and differs 68PDF Image | Operation and Control of Pressure Swing Adsorption Systems
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