间歇过程的批内自优化控制

针对间歇过程的实时优化问题, 提出了一种基于自优化控制的批内优化方法. 以测量变量的线性组合为被控变量, 在单批次内跟踪控制被控变量实现间歇过程的实时优化. 根据是否在间歇过程的不同阶段切换被控变量, 给出了两种自优化控制策略, 对每种策略又分别提出两种设定轨线选取方案. 为求解这些情形下的最优被控变量(组合矩阵), 以最小化平均经济损失为目标, 推导了组合矩阵和经济损失之间的函数关系, 分别将其描述为相应的非线性规划问题. 在此基础上, 进一步引入了扩张组合矩阵, 将这些非线性规划问题归纳为求解扩张组合矩阵的一致形式(扩张组合矩阵具有不同的结构约束), 并推导得到了其中一种方案的解析解计算方法. 以一个间歇反应器为研究对象, 验证了方法的有效性.

Within-batch Self-optimizing Control for Batch Processes

For real-time optimization of uncertain batch processes, a within-batch self-optimizing control (SOC) approach is proposed. In this approach, measurement combinations are selected as controlled variables, which are tracked at time-varying setpoints along batch operations. Regarding whether the controlled variables are switched at different batch phases, two self-optimizing control strategies are given, both of which further contain two schemes in terms of the computation of setpoint trajectory. To solve the optimal controlled variables (combination matrices), the average economic loss is considered as the to-be-minimized cost function, then the nonlinear programming problems are formulated by establishing the relationships between the loss and combination matrices. Based on these results, the extended combination matrix is introduced, then different nonlinear programming problems are uniformed as one problem for solving the optimal extended combination matrix (with different structural constraints). Among these cases, the analytical solution of one option is further derived. A batch reactor is studied to show the effectiveness of the proposed approach.