Lyapunov exponents with Model Predictive Control for exothermic batch reactors

Kähm, Walter; Vassiliadis, Vassilios V.

doi:10.1016/j.ifacol.2018.09.337

Cited by 7 publications

(7 citation statements)

References 5 publications

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“…The verication of Lyapunov exponents, evaluated with the optimal values for and t lyap found above, with respect to the point of loss of stability is carried out for reaction schemes 1 and 2. Similarly to the results shown in Kähm and Vassiliadis (2018a), once it is shown that Lyapunov exponents give a reliable prediction of system stability, this criterion can be applied to advanced control schemes such as MPC.…”

Section: Verication Of Lyapunov Exponents For System Stabilitymentioning

confidence: 63%

“…In this section the structure of common MPC schemes, as well as the scheme embedding Lyapunov exponents as presented in Kähm and Vassiliadis (2018a), is outlined. The basic concepts of MPC are described and the reformulation of the problem for such control schemes is shown.…”

Section: Model Predictive Control With Lyapunov Exponentsmentioning

confidence: 99%

“…The implementation of Model Predictive Control (MPC) with an embedded stability criterion was achieved in Kähm and Vassiliadis (2018b), Kähm and Vassiliadis (2018a) and Rossi et al (2015). These implementations enabled an increased eciency of exothermic batch processes while keeping the process under control at all times.…”

mentioning

confidence: 99%

“…Lyapunov exponents quantify the chaotic nature of processes by measuring the divergent or convergent nature with respect to the relevant system variables (Strozzi and Zaldívar, 1994;Melcher, 2003). This work focuses on the extension of Lyapunov exponents, based on the work given in Kähm and Vassiliadis (2018a).…”

mentioning

confidence: 99%

“…Other stability criteria are present in literature, as was discussed in Kähm and Vassiliadis (2018b) and Kähm and Vassiliadis (2018a). It was shown in both that the commonly used divergence criterion does not give reliable predictions on system stability for nonlinear nonsteady-state processes.…”

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confidence: 99%

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Optimal Laypunov exponent parameters for stability analysis of batch reactors with Model Predictive Control

Kähm

Vassiliadis

2018

Computers & Chemical Engineering

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Thermal runaways in exothermic batch reactions are a major economic, health and safety risk in industry. In literature most stability criteria for such behaviour are not reliable for nonlinear non-steady state systems. In this work, Lyapunov exponents are shown to predict the instability of highly nonlinear batch processes reliably and are hence incorporated in standard MPC schemes, leading to the intensication of such processes. The computational time is of major importance for systems controlled by MPC. The optimal tuning of the initial perturbation and the time frame reduces the computational time when embedded in MPC schemes for the control of complex batch reactions. The optimal tuning of the initial perturbation and time horizon, dening Lyapunov exponents, has not been carried out in literature so far and is here derived through sensitivity analyses. The computational time required for this control scheme is analysed for the intensication of complex reaction schemes.

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Section: Verication Of Lyapunov Exponents For System Stabilitymentioning

confidence: 63%

Section: Model Predictive Control With Lyapunov Exponentsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Optimal Laypunov exponent parameters for stability analysis of batch reactors with Model Predictive Control

Kähm

Vassiliadis

2018

Computers & Chemical Engineering

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Thermal stability criterion of complex reactions for batch processes

Kähm

Vassiliadis

2019

Chemical Engineering Research and Design

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Thermal stability of batch processes is a major factor for the safe and efficient production of polymers and pharmaceutical chemicals. The prediction of the thermal stability for such processes was shown in Kähm and Vassiliadis (2018d) to be unreliable with most stability criteria found in literature also presenting a novel criterion, K, which was shown to give reliable stability predictions for single reactions of higher order. This work provides a detailed derivation for the generalization of thermal stability criterion K applied to reaction networks of arbitrary complexity, consisting of parallel and competing reactions of both exothermic and endothermic nature. The generalized thermal stability criterion K is then applied to Model Predictive Control (MPC) frameworks to intensify batch processes in a safe manner, reducing the time required to reach the target conversion. Several illustrative computational case studies are presented, highlighting the proposed methodology and verifying its validity.

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Chaos measure dynamics in a multifactor model for financial market predictions

Vogl

2024

Communications in Nonlinear Science and Numerical Simulation

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Lyapunov exponents with Model Predictive Control for exothermic batch reactors

Cited by 7 publications

References 5 publications

Optimal Laypunov exponent parameters for stability analysis of batch reactors with Model Predictive Control

Optimal Laypunov exponent parameters for stability analysis of batch reactors with Model Predictive Control

Thermal stability criterion of complex reactions for batch processes

Chaos measure dynamics in a multifactor model for financial market predictions

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