中文摘要：

在生产过程中，间歇反应以其灵活多变的特性在制备多种类型的产品中占有十分重要的地位。近年来，间歇反应过程优化问题得到了广泛的关注，然而，由于间歇反应过程自身所具有的强非线性、缺少稳态操作条件、反应过程的不确定性等特点，很难提出有效的自动控制和优化操作的方案。一般而言，间歇过程的优化方案可以采用两个基本步骤：

英文摘要：

A complex exothermic batch reactor model was developed by using structure approaching hybrid neural networks （SAHNN）. The optimal reactor temperature profiles were obtained via the PSO-SQP algorithm solving maximum product concentration problem based on recurrent neural network （RNN）. Considering model-plant mismatches and unmeasured disturbances, a novel extended integral square error index （EISE） was proposed, which introduced mismatches of model-plant into the optimal control profile. The approach used a feedback channel for the control and therefore dramatically enhanced the robustness and anti-disturbance performance. The stability analysis of the one-step-ahead control strategy through SAHNN-based model was described based on Lyapunov theory in detail. The result fully demonstrated the effectiveness of the proposed optimal control profile.