دانلود مقاله ISI انگلیسی شماره 92307
ترجمه فارسی عنوان مقاله

افزایش سرعت بهینه سازی زمان واقعی با برآورد دولت های پایدار در فاز گذرا با استفاده از شناسایی سیستم های غیرخطی

عنوان انگلیسی
Speed-up of Iterative Real-Time Optimization by Estimating the Steady States in the Transient Phase using Nonlinear System Identification
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
92307 2017 6 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : IFAC-PapersOnLine, Volume 50, Issue 1, July 2017, Pages 11269-11274

ترجمه کلمات کلیدی
بهینه سازی زمان واقعی بهینه سازی ایده آل، سازگاری اصلاح کننده شناسایی سیستم غیرخطی
کلمات کلیدی انگلیسی
Real-Time Optimization; Iterative Optimization; Modifier Adaptation; Nonlinear System Identification;
پیش نمایش مقاله
پیش نمایش مقاله  افزایش سرعت بهینه سازی زمان واقعی با برآورد دولت های پایدار در فاز گذرا با استفاده از شناسایی سیستم های غیرخطی

چکیده انگلیسی

Iterative Real-Time Optimization (RTO) has gained increasing attention in the context of model-based optimization of the operating points of chemical plants in the presence of plant-model mismatch. In all iterative RTO schemes, it is necessary to wait until the plant has reached a steady-state to obtain the required information on plant performance and constraint satisfaction which leads to slow convergence in the case of processes with slow dynamics. It has recently been proposed to use a linear black-box model that is identified online to predict the steady-state values of the plant during the transient between different stationary operating points; these values are then employed in the modifier adaptation with quadratic approximation to drive the process to its optimum (Gao et al., 2016). In this contribution, this idea is extended by integrating nonlinear system identification into iterative RTO. Specifically, a Nonlinear Output Error (NOE) model is proposed to describe the dynamics of the process, thus providing a faster prediction of the steady-state of the plant. A robust scheme for the estimation of the model parameters is proposed. The performance of the strategy is illustrated by simulation studies of a continuous stirred-tank reactor. By means of the proposed methodology a fast convergence to the plant optimum can be achieved despite plant-model mismatches.