State feedback synthesis for on-line optimization of batch reactors with a non-affine manipulated input and free terminal time

Паланки, Сринивас; Rahman, A.K.M.S.

doi:10.1109/acc.1994.735136

Cited by 2 publications

(2 citation statements)

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“…In a series of papers by Palanki and Rahman (Palanki et al, 1993;Palanki and Rahman, 1994;Palanki, 1996, 1998) a method is introduced that provides a geometric approach to handling batch optimization. They show how to develop feedback laws for end-point optimization problems under a variety of state space variations.…”

Section: Real-time Dynamic Optimization Of Non-linear Batch Systemsmentioning

confidence: 99%

Real‐time Dynamic Optimization of Non‐linear Batch Systems

2006

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In this paper, a methodology for designing and implementing a real time optimizing controller for non-linear batch processes is discussed. The controller is used to optimize the system input and state trajectories according to a cost function. An interior point method with penalty function is used to incorporate constraints into a modifi ed cost functional, and a Lyapunov-based extremum seeking approach is used to compute the trajectory parameters. Smooth trajectories were generated with reduced computing time compared to many optimizations in literature. In this paper, the theory is applied to general non-fl at non-linear systems in a true on-line optimization.Dans cet article, on étudie une méthodologie pour la conception et l'implantation d'un contrôleur d'optimisation en temps réel de procédés discontinus non linéaires. Le contrôleur sert à optimiser l'entrée du système et les trajectoires d'état d'après une fonction de coûts. Pour calculer par ordinateur les paramètres de trajectoire, on recourt à une méthode à points intérieurs avec une fonction de pénalités pour incorporer des contraintes dans une méthode de recherche des extrêmes lyapunovienne et une fonctionnelle de coût modifi ée. Des trajectoires lisses ont été produites avec un temps de calcul réduit comparativement à de nombreuses optimisations de la littérature scientifi que. Dans cet article, la théorie est appliquée à des systèmes non linéaires non plats généraux dans une véritable optimisation en ligne.

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Section: Real-time Dynamic Optimization Of Non-linear Batch Systemsmentioning

confidence: 99%

Real‐time Dynamic Optimization of Non‐linear Batch Systems

2006

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“…To try and compensate for the amount of computing time required, the profiles may be parameterized to known trajectories that have met with success (see (Visser et al, 2000)). In a series of papers by Palanki and Rahman (Palanki et al, 1993), (Palanki and Rahman, 1994), (Rahman and Palanki, 1996), and (Rahman and Palanki, 1998) a method is introduced that provides a geometric approach to handling batch optimization. They show how to develop feedback laws for end-point optimization problems under a variety of state space variations.…”

Section: Introductionmentioning

confidence: 99%