Stabilization of an unstable tubular reactor by nonlinear passive output feedback control

Reyes, Hugo A. Franco-de los; Schaum, Alexander; Meurer, Thomas; Álvarez, Jesús

doi:10.1016/j.jprocont.2020.07.005

Cited by 11 publications

(6 citation statements)

References 36 publications

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“…In (A1) T, c : [0, 1] × R + → R with T(s, t) representing the reactor temperature at s ∈ [0, 1] and time t ≥ 0, c(s, t) the concentration, D being the diffusion coefficient, v the superficial velocity (assumed to be constant), η the heat interchange coefficient between the cooling jacket with temperature T c (s, t) (that can be used as a control input [27]), δ the adiabatic temperature rise, ρ : R + → R + the reaction rate function, γ the Arrhenius coefficient, and T e , c e the (constant) feed temperature and concentration, respectively.…”

Section: Appendix a Tubular Reactor Modelmentioning

confidence: 99%

“…Considering in a first approximation that the temperature deviation can be neglected (e.g., due to some appropriate control through the cooling jacket temperature [27]) one ob-…”

Section: Appendix a Tubular Reactor Modelmentioning

confidence: 99%

“…To the author's knowledge, this is the first time such a comparison with reduced order observers is carried out, in particular for this class of systems. The result is an inductive step towards the consideration of distributed parameter models involving transport-reaction mechanisms as typically found in chemical engineering applications [7,[24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

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Autoencoder-Based Reduced Order Observer Design for a Class of Diffusion-Convection-Reaction Systems

Schaum¹

2021

Algorithms

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The application of autoencoders in combination with Dynamic Mode Decomposition for control (DMDc) and reduced order observer design as well as Kalman Filter design is discussed for low order state reconstruction of a class of scalar linear diffusion-convection-reaction systems. The general idea and conceptual approaches are developed following recent results on machine-learning based identification of the Koopman operator using autoencoders and DMDc for finite-dimensional discrete-time system identification. The resulting linear reduced order model is combined with a classical Kalman Filter for state reconstruction with minimum error covariance as well as a reduced order observer with very low computational and memory demands. The performance of the two schemes is evaluated and compared in terms of the approximated L2 error norm in a numerical simulation study. It turns out, that for the evaluated case study the reduced-order scheme achieves comparable performance with significantly less computational load.

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Section: Appendix a Tubular Reactor Modelmentioning

confidence: 99%

“…Considering in a first approximation that the temperature deviation can be neglected (e.g., due to some appropriate control through the cooling jacket temperature [27]) one ob-…”

Section: Appendix a Tubular Reactor Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Autoencoder-Based Reduced Order Observer Design for a Class of Diffusion-Convection-Reaction Systems

Schaum¹

2021

Algorithms

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“…An optimal integral SMC‐based CNF is suggested for an electrostatic micro‐mirror [27]. An unstable reactor can be stabilized by a passive output feedback control [28].…”

Section: Introductionmentioning

confidence: 99%

An innovative algorithm for tuning of composite nonlinear feedback control in continuous‐time systems

Vazani

Ghaffari

2022

Asian Journal of Control

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The transient response improvement is the most crucial feature of the composite nonlinear feedback (CNF) controllers. This study proposes a novel CNF tuning method for systems subject to saturation. To achieve the goals, the linear part is optimally obtained via a performance index and the linear matrix inequality (LMI). Then, employing the passivity property, a heuristic way is suggested to adjust the nonlinear term. Thus, the automatic and online features would be the key novelties of this algorithm compared with the offline, trial and error, or nonautomatic ones. Some systems are simulated to evaluate the technique and compare with the existing methods. The outcomes confirm that the proposed tuning yields outstanding improvement concerning the aforementioned systems.

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“…From this set of possible equilibria, the unstable steady state is usually of industrial interest as it corresponds to a high reaction efficiency with admissible temperature. Thus, many studies have been dedicated to the control of tubular reactors described by partial differential equations models around the unstable steady state profile [1,6,8,13,12,22,24,28,32].…”

mentioning

confidence: 99%

A thermodynamic approach to the stabilization of tubular reactors

Zhou

Hamroun

Gorrec

et al. 2021

Journal of Process Control

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Stabilization of an unstable tubular reactor by nonlinear passive output feedback control

Cited by 11 publications

References 36 publications

Autoencoder-Based Reduced Order Observer Design for a Class of Diffusion-Convection-Reaction Systems

Autoencoder-Based Reduced Order Observer Design for a Class of Diffusion-Convection-Reaction Systems

An innovative algorithm for tuning of composite nonlinear feedback control in continuous‐time systems

A thermodynamic approach to the stabilization of tubular reactors

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