Performance Analysis of Perturbation-Based Methods for Real-Time Optimization

Abstract

are the base on which any RTO system is built. A number of researchers have investigated the design and interaction of these two subsystems, particularly with respect to plant/model mismatch. The Two-Phase approach (Chen and Joseph, 1987) is the most widely used method for model updating and modelbased optimization in RTO. In this approach the optimization problem and parameter estimation problem are solved separately. Although this Two-Phase approach attempts to solve the RTO problem by updating the imperfect model, it will not necessarily converge to the correct optimum (Durbeck, 1965;Biegler et al., 1985;Forbes et al., 1994). To address this issue, methods have been proposed to deal explicitly with plant/model mismatch. These methods fall into two distinct classes: (1) those that modify the RTO problem directly; and (2) those that use adaptive control ideas modifi ed to suit RTO applications.This paper provides a comprehensive performance analysis approach for Real-Time Optimization (RTO) technologies, which incorporates systematic approaches to estimating bounds on the convergence behaviour and performance effects of on-line experiments used by a given RTO approach. The performance analysis method is illustrated by an investigation of the conventional two-phase approach and representative techniques drawn from the three main classes of perturbation-based RTO methods which attempt to directly compensate for plant/model mismatch through adaptation. The proposed approach is applied to two simulation-based case studies: a heat exchanger system and a continuous bioreactor.On présente dans cet article une méthode complète d'analyse de performance pour les technologies d'optimisation en temps réel (RTO), qui comporte des approches systématiques pour l'estimation des bornes de convergence et les effets de performance sur des expériences en ligne utilisées dans une approche RTO donnée. L'analyse de performance est illustrée par une étude de l'approche conventionnelle à deux phases et des techniques représentatives issues des trois catégories principales de méthodes RTO basées sur des perturbations et qui tentent de compenser directement l'incompatibilité usine/modèle par l'adaptation. La méthode proposée est appliquée à deux études de cas basées sur des simulations : un système d'échangeur de chaleur et un bioréacteur continu.

Modifier-Adaptation Methodology for Real-Time Optimization

“…Comparisons between different RTO approaches have been published in [28], and more recently in [18,98].…”

“…In the context of RTO, several methods for estimating experimental gradients have been proposed. These methods have been compared by several authors [58,98]. A distinction can be made between steady-state perturbation methods and dynamic perturbation methods.…”

“…The RTO system attempts to track the plant optimum changing at low frequency to maintain the plant at its most profitable operating point [98]. Real-time optimization, on-line optimization and optimizing control are different terms that have been used in the literature to designate the same purpose, which is the continuous reevaluation and alteration of operating conditions of a process so that economic productivity is maximized subject to operational constraints [2,46,63].…”

Modifier Adaptation for Real-Time Optimization—Methods and Applications

“…Several methods are available for estimating plant gradients [57][58][59][60]. These methods can be classified as steady-state perturbation methods that use only steady-state data, and dynamic perturbation methods that use transient data.…”

“…The same approach was also used by Golden and Ydstie [32] for estimating the first-and second-order derivatives of a SISO plant. Zhang and Forbes [60] compared the optimizing controllers proposed in [70] and [32] with ISOPE and the two-step approach.…”