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Assessment and Future Directions of Nonlinear Model Predictive ...

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A <strong>Nonlinear</strong> <strong>Model</strong> <strong>Predictive</strong> Control Framework as Free S<strong>of</strong>tware 235Table 1. <strong>Model</strong> dataC A0 10. mol/lC p ,C pj 4184. Jkg −1 K −1F 0 ,F 4.0 l/minE a/R 10080. Kk 0 6.20 × 10 14 mol m −3 s −1T 0 21.0◦ C◦ CT j0 26.0U 900. Wm −2 K −1V j 0.014 m 3α j 7.0 × 10 5 J/K(−∆H r) 33488. J/molρ, ρ j 1000. kg/m 3Table 2. Typical steady statesSteady states lower upperh 0.30 0.30 mC A 7.82 4.60 mol/lT r 31.5 40.1 ◦ CT j 28.0 28.0 ◦ CF j 14.0 48.8 l/minThe reactor temperature dynamics is described bydT rdt = F 0V (T 0 − T r ) −UAρC p V (T r − T j )+ (−∆H r)k 0 e −Ea/(R Tr) , (15)ρC p<strong>and</strong> the jacket temperature dynamics is described bydT jdt = 1[]ρ j C pj F j (T j0 − T j )+ UA(T r − T j ) , (16)ρ j C pj V j + α jwhere C pj is the specific heat capacity <strong>of</strong> the coolant, <strong>and</strong> F j is the coolantflow rate. The heat transfer area is calculated from A = π(r 2 +2rh)withr =0.237 m. Finally, the coefficient α j in (16) st<strong>and</strong>s for the contribution <strong>of</strong>the wall <strong>and</strong> spiral baffle jacket thermal capacitances. A summary <strong>of</strong> the datamodel is given in Table 1. Two typical steady states <strong>of</strong> this system, one stableat a lower temperature <strong>and</strong> one unstable at an upper temperature, are given inTable 2. Further details on this model are provided in [23, 24].3.1 Simulation ResultsThe output variables are the reactor level <strong>and</strong> the temperature, y T =[hT r ],<strong>and</strong> the controls are the coolant flow rate <strong>and</strong> the outlet flow rate, u T =[F j F ].The following operating limits on the outputs <strong>and</strong> the controls are considered:0.08 h 0.41 m; T r 0; 0 F j 76 l/min; <strong>and</strong> 0 F 12 l/min.The results presented in Figure 2 were obtained assuming that the modelis perfect <strong>and</strong> that all the state variables are measured. The output terminalconstraints, integral action, control move rate constraints <strong>and</strong> constraintrelaxation were turned <strong>of</strong>f. These results were obtained using predictive horizons(p, m) =(20, 5), a sampling time <strong>of</strong> 30 s, <strong>and</strong> diagonal weighting matricesQ yk = diag(5 × 10 2 , 10 5 )<strong>and</strong>Q uk = diag(10 −1 , 10 −3 ), k =1, ··· ,p.

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