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Robust simulation and design using semi-infinite programs with implicit functions

机译:使用具有隐式函数的半无限程序进行稳健的仿真和设计

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摘要

A method is presented for guaranteeing robust steady-state operation of chemical processes using a model-based approach, taking into account uncertainty in the model parameters and disturbances in the process inputs. Intractable constrained max-min optimisation formulations have been proposed for this problem in the past. A new approach is presented in which the equality constraints (process model equations) are solved numerically for the process variables as implicit functions of the uncertain parameters and controls. The problem is then formulated as a semi-infinite program (SIP) constrained only by the performance specifications as semi-infinite inequality constraints. A rigorous, finite s-optimal convergent algorithm for solving such SIPs is proposed, making no assumptions on convexity, which makes use of the novel developments of parametric interval-Newton methods for bounding implicit functions, and novel developments in McCormick relaxations of algorithms.
机译:提出了一种基于模型的方法,其中考虑了模型参数的不确定性和过程输入中的干扰,从而保证了化学过程的稳定稳态运行。过去已经针对此问题提出了棘手的约束最大-最小优化公式。提出了一种新方法,其中以数值形式求解过程变量的等式约束(过程模型方程),作为不确定性参数和控件的隐式函数。然后将问题表述为仅受性能规格约束的半无限程序(SIP)作为半无限不等式约束。提出了一种求解此类SIP的严格的,有限的s最优收敛算法,该算法没有对凸度做出任何假设,而是利用参数区间牛顿方法的新颖发展来界定隐函数,并利用了McCormick松弛算法的新颖发展。

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