基于改进SAA的串联打浆过程优化控制策略

The Optimal Control Strategy of Serial Refining Process Based on Improved SAA

中文关键词: 打浆过程  模拟退火算法  过程优化  多目标优化

英文关键词: pulp refining process  simulated annealing algorithm  process optimization  multi-objective optimization

中文摘要:

      目的 为了获得打浆过程最优的过程控制变量，以保证打浆品质优、产量高、成本低的经济性生产。方法 选择流量、浓度、盘磨电流为决策变量，分别以打浆度和湿质量的稳定性、单位时间磨浆绝干量和单位磨浆量的成本作为指标建立多目标优化模型，提出一种改进的动态自适应模拟退火算法（DASAA），并基于Matlab优化仿真求解。结果 案例仿真结果表明，优化前后实际效果显著，理论上不仅打浆品质更优，而且产量提高约0.73 t/h，成本下降约4.25 元/t。结论 基于改进优化算法的串联打浆过程优化控制策略，相对于传统的决策变量经验性设定控制能更好地满足生产要求，且在一定程度上能实现高品质、高产量、低成本的折中优化。

英文摘要:

      The work aims to obtain the optimal process control variables for the pulp refining process to ensure the economical production with superior beating quality, high yield and low cost. With flow, concentration and disc refiner's current as decision variables, the multi-objective optimization model was established by regarding the stability of beating degree and wet weight, the amount of dry weight of beaten pulp in unit time and the refining cost per unit as the modeling indexes, an improved dynamic adaptive simulated annealing algorithm (DASAA) was proposed and the simulation solution was optimized based on Matlab. The case simulation results showed that the actual effects before and after the optimization were significant; in theory, not only the refining quality was better, but the yield was increased by 0.73 t/h and the cost was reduced by about 4.25 yuan/t. Compared with the empirical setting control of traditional decision variable, the optimization control strategy of serial refining process based on the improved optimization algorithm can better meet the production requirements, and to some extent achieve the trade-off optimization between high quality, high yield and low cost.