Qualitative Analysis for Homogeneous Azeotropic Distillation. 2. Bifurcation Analysis

Dorn, Cornelius; Morari, Manfred

doi:10.1021/ie010726j

Cited by 15 publications

(15 citation statements)

References 29 publications

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“…Hernjak et al12 proposed a qualitative process operability analysis method based on three main process characteristics: the degree of nonlinearity, process dynamics and degree of interaction between loops. Research effort has also concentrated on the nonlinear phenomena that is known to generate operability difficulties such as multiple equilibrium points, limit cycles, chaotic behavior and bifurcations, e.g.,13–17 However, none of the above open‐loop methods addresses the plant‐wide operability analysis problem from a network perspective.…”

Section: Introductionmentioning

confidence: 99%

Dynamic operability analysis of nonlinear process networks based on dissipativity

et al. 2009

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Most modern chemical plants are complex networks of multiple interconnected nonlinear process units, often with multiple recycle and by-pass streams and energy integration. Interactions between process units often lead to plant-wide operability problems (i.e., difficulties in process control). Plant-wide operability analysis is often difficult due to the complexity and nonlinearity of the processes. This article provides a new framework of dynamic operability analysis for plant-wide processes, based on the dissipativity of each process unit and the topology of the process network. Based on the concept of dissipative systems, this approach can deal with nonlinear processes directly. Developed from a network perspective, the proposed framework is also inherently scalable and thus can be applied to large process networks. V V C 2009 American Institute of Chemical Engineers AIChE J, 55: [963][964][965][966][967][968][969][970][971][972][973][974][975][976][977][978][979][980][981][982] 2009 Keywords: plant-wide control, nonlinear systems, process networks, process operability IntroductionProcess control has been playing an increasingly important role in the process industries as more process integration and tighter operating conditions are putting greater demands on control system performance. The traditional approach to process design and control has been to perform the design of the process and the control system sequentially.1 As little consideration is given to dynamic operability in the process design stage, the outcome of this approach sometimes is a plant whose dynamic characteristics lead to serious operating difficulties associated with significant economic penalties.2 It is well known that a process design fundamentally determines the inherent operability properties of the process since it imposes limitations on control performance regardless of what control method is implemented. Therefore, process operability analysis should be performed in the process design stage for better integration of process design and control. 1 Modern chemical plants have two important features: (1) they are networks of significant number of process units with recycle and heat integration configurations; (2) process units are generally nonlinear. Interactions between the process units are often the main causes of operability problems. As such, it is important to develop appropriate tools to quantitatively assess the effects of nonlinear dynamics of process units and the interactions between them on plant-wide operability. 3 In the past two decades, a number of operability analysis tools have been reported. Many of these were developed for linear processes, based on, e.g., process zero dynamics, minimum singular values and loop interactions. [4][5][6] For nonlinear processes, a direct approach to operability analysis is to solve a dynamic performance optimisation problem numerically. Although this approach allows seamless integration of process and control design, 6-9 the complexity of the resulting problem grows quickly with t...

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Section: Introductionmentioning

confidence: 99%

Dynamic operability analysis of nonlinear process networks based on dissipativity

et al. 2009

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“…The applications of bifurcation analysis as a powerful nonlinear system analysis tool for chemical processes have been widely reported. [215][216][217][218][219][220][221][222][223][224][225] Morari suggested that bifurcation analysis should be used in controllability analysis for nonlinear systems. 226 Input/output multiplicity is a complex phenomenon that can be encountered in chemical processes and will adversely affect the performance of the closed-loop system, subject to the changing operating conditions.…”

Section: Bifurcation Analysis-based Methods For Process Designmentioning

confidence: 99%

An overview on controllability analysis of chemical processes

2011

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Controllability is one of the most important aspects of chemical process operability, because it can be used to assess the attainable operation of a given process and improve its dynamic performance. The purpose of this article is to outline the main methodologies that have been developed to deal with the assessment of process controllability and the improvement of its controllability characteristics. Several existing controllability assessment methods are reviewed and discussed. For improving the controllability characteristic of a process, there are two main design methods: the optimization-based method and the controllability indices-based anticipating sequential method. Advantages and disadvantages of these techniques are discussed. It has been emphasized that bifurcation analysis, as a powerful nonlinear analysis tool, could provide important guidance for making processes more controllable by eliminating or avoiding some undesirable behaviors of processes. Further challenges and developments in the field of process controllability are identified.

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“…Applications are available in the chemical engineering literature. [36][37][38][39] Interval methodology is also applied (see, for example, Tolsma and Barton, 40 Gehrke and Marquardt, 41 or Gwaltney et al 42 ).…”

Section: Search For Bifurcation Points With Interval Methodologymentioning

confidence: 99%

Finding limiting flows of batch extractive distillation with interval arithmetic

et al. 2006

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Qualitative Analysis for Homogeneous Azeotropic Distillation. 2. Bifurcation Analysis

Cited by 15 publications

References 29 publications

Dynamic operability analysis of nonlinear process networks based on dissipativity

Dynamic operability analysis of nonlinear process networks based on dissipativity

An overview on controllability analysis of chemical processes

Finding limiting flows of batch extractive distillation with interval arithmetic

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