Combination of steady state optimization with dynamic state optimization was presented to optimize ethylene epoxidation reactor.

提出了乙烯氧化反应器定态和动态优化相结合的优化策略。

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The iterative learning control is studied for the procedure of industrial process steady state optimization in order to improve the dynamic performance of control systems.

针对具有噪声的工业过程稳态优化进程，提出迭代学习控制以期改善控制系统的动态品质。

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By establishing a novel method for integrating transient stability constraints into conventional steady-state ATC, the dynamic ATC problem is successfully formulated as an optimization problem.

建立了在传统的静态AT C模型中加入暂态稳定约束的有效方法，并在此基础上给出了动态atc问题的优化计算模型。

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