Process operational safety via model predictive control: Recent results and future research directions

Albalawi, Fahad; Durand, Helen; Christofides, Panagiotis D.

doi:10.1016/j.compchemeng.2017.10.006

Cited by 27 publications

(14 citation statements)

References 75 publications

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“…Incorporating a stability constraint as a hard constraint for continuous systems controlled by MPC has been considered in literature (Zhang et al, 2018;Albalawi et al, 2018Albalawi et al, , 2017.…”

Section: Discussionmentioning

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: Discussionmentioning

confidence: 99%

“…A good review on stability criteria embedded in MPC algorithms for continuous systems is given in Albalawi et al (2018). The work presented therein is useful for many continuous systems in industry.…”

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confidence: 99%

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

Kähm

Vassiliadis

2018

Computers & Chemical Engineering

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“…Operability metrics that can simultaneously assess multiple operational aspects of such systems are very limited (e.g., flexibility, operability, safety, controllability, availability, reliability, maintenance). Some examples for this purpose include: the combined flexibility–reliability index to simultaneously cope with stochastic parameter variations and equipment failures proposed by Thomaidis and Pistikopoulos, 89 the integrated control‐safety system design to account for operational safety via model predictive control proposed by Albalawi et al, 90 and so on. One of the key characteristics of PI is to encourage novel technology development. The question thus arises on how to assess the practical operational performance of a brand new process with a lack of historical data (this question also exists for cost estimation and safety evaluation).…”

Section: Research Opportunities and Perspectivesmentioning

confidence: 99%

Operability and control in process intensification and modular design: Challenges and opportunities

2021

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In this article, the importance of considering operability and control criteria in the analysis and design of intensified and modular processes is discussed. We first analyze the impact on operability of key factors including: (i) degrees of freedom, (ii) process constraints, (iii) numbering up vs. scaling up, and (iv) dynamic/periodic operation. Comparative examples are presented to showcase the pros and cons in intensified/modular systems vs. their conventional counterparts from operability and control aspects. Then we look into metrics and tools to address these challenges such as: (i) flexibility analysis, (ii) operability‐based design, and (iii) advanced model‐based control. Considering different conceptual design stages as synthesis intensification, steady‐state design, and dynamic operational optimization, we highlight the need to incorporate different levels of operability considerations. Future research opportunities and perspectives are also identified, particularly emphasizing the importance of a holistic strategy for integrated design, operability, and control of intensified and modular process systems.

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“…Stability criteria based on Lyapunov functions were implemented in systems operating at steady state before, for which a good review is given by Albalawi et al (2018). For continuous systems in industry good results were obtained with such an approach (Zhang et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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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Process operational safety via model predictive control: Recent results and future research directions

Cited by 27 publications

References 75 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

Operability and control in process intensification and modular design: Challenges and opportunities

Thermal stability criterion of complex reactions for batch processes

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