Research Article
Data-Driven Optimal Control for Pulp Washing Process Based on Neural Network
Table 9
Optimization results of the pulp washing process.
| | Independent variables | Inlet pulp consistency (kg/m3) | Inlet pulp flow (m3/h) | Inlet water flow (m3/h) | DF | Weight |
| | Before optimization | 2.1 | 117.5 | 34.7 | 0.5 | ω 1 = 0.4, ω2 = 0.3, ω3 = 0.3, β = 0.5 | | After optimization | 2.4 | 129.7 | 25 | 3.2 |
| | Dependent variables | Baume degree (Be) | Residual soda (g/L) | Outlet slurry (T/h) | Cost (yuan/ton) | Weight |
| | Before optimization | 7.2546 | 2.398 | 246.75 | 13.2 | ω 1 = 0.4, ω2 = 0.3, ω3 = 0.3, β = 0.5 | | After optimization | 9.3003 | 2.1848 | 311.28 | 10.9 |
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