Use of transient measurements for the optimization of steady-state performance via modifier adaptation
Use of transient measurements for the optimization of steady-state performance via modifier adaptation
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DOI：
10.1021/ie401392s
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发表时间：
2014-04
影响因子：
4.2
通讯作者：
G. François;D. Bonvin
中科院分区：
文献类型：
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作者：
G. François;D. Bonvin
实时优化（RTO）方法使用测量值来抵消不确定性的影响，并将工厂推向最佳状态。RTO方案的不同之处在于将测量纳入优化框架的方式。显式RTO方案反复解决静态优化问题，每次迭代都需要将工厂的瞬态操作转换为稳态。相比之下，隐式RTO方法使用瞬态测量，使工厂在一个单一的迭代稳态最优，提供了一套积极的约束是已知的。本文认为显式RTO计划“修改器自适应”（MA），并提出了一个框架，允许使用瞬态测量的稳态优化的目的。它表明，收敛到工厂的最佳可以实现在一个单一的瞬态操作提供的植物梯度可以准确地估计。通过连续搅拌釜式反应器的模拟实例说明了该方法。收敛所需的时间是…
Real-time optimization (RTO) methods use measurements to offset the effect of uncertainty and drive the plant to optimality. RTO schemes differ in the way measurements are incorporated in the optimization framework. Explicit RTO schemes solve a static optimization problem repeatedly, with each iteration requiring transient operation of the plant to steady state. In contrast, implicit RTO methods use transient measurements to bring the plant to steady-state optimality in a single iteration, provided the set of active constraints is known. This paper considers the explicit RTO scheme “modifier adaptation” (MA) and proposes a framework that allows using transient measurements for the purpose of steady-state optimization. It is shown that convergence to the plant optimum can be achieved in a single transient operation provided the plant gradients can be estimated accurately. The approach is illustrated through the simulated example of a continuous stirred-tank reactor. The time needed for convergence is of th...