Modelling, Optimization and Control of Nonlinear Processes

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".

Deadline for manuscript submissions: closed (25 January 2024) | Viewed by 1868

Special Issue Editors


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Guest Editor
Department of Chemical Engineering, Faculty Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia
Interests: advanced and non linear control of process systems; modelling and process control of UF filtration systems to produce clean water; modelling and process control of fuel cell systems; advanced mathematical modelling of gas olefin polymerization in fluidized-bed catalytic reactor; advanced control for semi-active car suspension system; optimisation of chemical process systems; development of software for online process control; artificial intelligence for modelling and control of process systems; process control
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Guest Editor
Department of Chemical Engineering, Faculty of Engineering & Informatics, University of Bradford, Bradford BD7 1DP, UK
Interests: dynamic modelling; simulation; optimisation and control of batch and continuous chemical processes with specific interests in distillation; industrial reactors; refinery processes; desalination; wastewater treatment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modelling of nonlinear processes has been and is still a constant challenge to the engineering community at large due to its inherent complexity, interactions, nonlinear dynamics and multivariate issues affecting the process behavior in such systems. Thus, in recent years, novel hybrid techniques involving first principles theory, empirical approaches, data-based regression and artificial- intelligence-based methods are being actively studied by researchers to handle the modelling of such nonlinear systems. Since the optimization and control of these nonlinear systems, in many cases, also depend on the accuracy of the models obtained, advanced research activities in these fields are also going through rapid development in research.

This Special Issue on “Modelling, Optimization and Control of Nonlinear Processes” aims to collect recent and high-quality research studies and review addressing these challenges. Topics include, but are not limited to, the following:

  • The development of improved modelling and hybrid methods for nonlinear processes
  • The development of advanced system identification and observers for nonlinear processes
  • Optimization techniques for nonlinear processes
  • The development of advanced control strategies for nonlinear processes
  • Online validation for modelling and control techniques for nonlinear processes
  • Review papers related to the above topics

Prof. Dr. Mohd Azlan Hussain
Prof. Dr. Iqbal M. Mujtaba
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • energy–water–food nexus
  • desalination
  • wastewater treatment
  • refinery processes
  • catalysis
  • membranes

Published Papers (1 paper)

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Research

22 pages, 1924 KiB  
Article
Pressure Swing Adsorption Plant for the Recovery and Production of Biohydrogen: Optimization and Control
by Jorge A. Brizuela-Mendoza, Felipe D. J. Sorcia-Vázquez, Jesse Y. Rumbo-Morales, Gerardo Ortiz-Torres, Carlos Alberto Torres-Cantero, Mario A. Juárez, Omar Zatarain, Moises Ramos-Martinez, Estela Sarmiento-Bustos, Julio C. Rodríguez-Cerda, Juan Carlos Mixteco-Sánchez and Hector Miguel Buenabad-Arias
Processes 2023, 11(10), 2997; https://doi.org/10.3390/pr11102997 - 18 Oct 2023
Cited by 3 | Viewed by 1518
Abstract
New biofuels are in demand and necessary to address the climate problems caused by the gases generated by fossil fuels. Biohydrogen, which is a clean biofuel with great potential in terms of energy capacity, is currently impacting our world. However, to produce biohydrogen, [...] Read more.
New biofuels are in demand and necessary to address the climate problems caused by the gases generated by fossil fuels. Biohydrogen, which is a clean biofuel with great potential in terms of energy capacity, is currently impacting our world. However, to produce biohydrogen, it is necessary to implement novel processes, such as Pressure Swing Adsorption (PSA), which raise the purity of biohydrogen to 99.99% and obtain a recovery above 50% using lower energy efficiency. This paper presents a PSA plant to produce biohydrogen and obtain a biofuel meeting international criteria. It focuses on implementing controllers on the PSA plant to maintain the desired purity stable and attenuate disturbances that affect the productivity, recovery, and energy efficiency generated by the biohydrogen-producing PSA plant. Several rigorous tests were carried out to observe the purity behavior in the face of changes in trajectories and combined perturbations by considering a discrete observer-based LQR controller compared with a discrete PID control system. The PSA process controller is designed from a simplified model, evaluating its performance on the real nonlinear plant considering perturbations using specialized software. The results are compared with a conventional PID controller, giving rise to a significant contribution related to a biohydrogen purity stable (above 0.99 in molar fraction) in the presence of disturbances and achieving a recovery of 55% to 60% using an energy efficiency of 0.99% to 7.25%. Full article
(This article belongs to the Special Issue Modelling, Optimization and Control of Nonlinear Processes)
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