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Processes
Special Issues
Contemporary Methods for Process Modelling and Control
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Contemporary Methods for Process Modelling and Control

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

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 12568

Special Issue Editors

Prof. Dr. Velislava Lyubenova

E-Mail Website
Guest Editor
Institute of Robotics, Bulgarian Academy of Science, Acad. G. Bonchev str. Bl. 2, 1113 Sofia, Bulgaria
Interests: bioengineering; modelling; monitoring; control; optimization; nonlinear processes; genetic algorithms
Prof. Dr. Olympia Roeva

E-Mail Website
Guest Editor
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
Interests: mathematical modelling; metaheuristic algorithms; process control; generalised nets; intuitionistic fuzzy sets; intercriteria analysis
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Maya Ignatova

E-Mail Website
Guest Editor
Institute of Robotics, Bulgarian Academy of Science, Acad. G. Bonchev str. Bl. 2, 1113 Sofia, Bulgaria
Interests: bioengineering; modelling; monitoring; control; optimization; nonlinear processes

Special Issue Information

Dear Colleagues,

We are pleased to invite you to publish materials related to innovative solutions for the advanced control of biotechnological, ecological, and chemical processes in scientific research and industrial applications.

These processes are currently the subject of intensive research with respect to the development of food and pharmaceutical industries, as well as studies of environmental phenomena. Process modelling is a mandatory initial stage in the research and synthesis of their control. The main goals are increasing the productivity of industrial processes and reducing the production costs. Regarding ecological processes, their modelling is very effective for predicting the dynamics of the development of various ecological disasters and ecological catastrophes (water pollution, air pollution, fire spread, etc.).

The general approach towards process modelling and control algorithm design is the application of the theory of dynamical systems tools.

This Special Issue “Contemporary Methods for Process Modelling and Control” is aimed at collecting studies related to the research areas mentioned above. Topics include, but are not limited to, the following:

  • Modelling the kinetics of beer and wine production processes;
  • Development of adaptive models for the monitoring of biotechnological processes;
  • Software sensors design for the monitoring and adaptive control of bioprocesses;
  • Interactive system for education in the modelling and control of bioprocesses;
  • Wastewater treatment monitoring modelling;
  • Air pollution modelling;
  • Fire-spread models;
  • Weather climate models.

Prof. Dr. Velislava Lyubenova
Dr. Olympia Roeva
Prof. Dr. Maya Ignatova
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

  • modelling
  • monitoring
  • advanced control
  • biotechnological
  • ecological and chemical processes

Published Papers (5 papers)

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Research

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17 pages, 1394 KiB  
Article
Method for Solving the Microwave Heating Temperature Distribution of the TE10 Mode
by Biao Yang, Hongbin Huang, Liexing Zhou and Huaiping Jin
Processes 2022, 10(7), 1377; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10071377 - 14 Jul 2022
Cited by 1 | Viewed by 1354
Abstract
Microwave heating is a process in which the electric, magnetic, and temperature fields are coupled with each other and are characterised by strong non-linearity, high time variability, and infinite dimensionality. This paper proposes a method for predicting the microwave heating temperature distribution of [...] Read more.
Microwave heating is a process in which the electric, magnetic, and temperature fields are coupled with each other and are characterised by strong non-linearity, high time variability, and infinite dimensionality. This paper proposes a method for predicting the microwave heating temperature distribution of the TE10 mode, because the traditional numerical calculation method is not conducive to designing microwave controllers. First, the spatial distribution of the main electromagnetic mode TE10 waves in a rectangular waveguide was analysed using the principal mode analysis method. An expression for the transient dissipated power and a heat balance equation with infinite-dimensional characteristics were constructed. Then, the microwave heating model was decomposed into electromagnetic and temperature field submodels. A time discretization approach was used to approximate the transient constant dielectric constant. The heating medium was meshed to solve the electric field strength and transient dissipated power in discrete domains, and the temperature distribution was obtained by substituting this value into the finite-dimensional temperature field submodel. Finally, the validity of the proposed numerical model was verified by comparing the results with the numerical results obtained with the conventional finite element method. The methodology presented in this paper provides a solid basis for designing microwave heating controllers. Full article
(This article belongs to the Special Issue Contemporary Methods for Process Modelling and Control)
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16 pages, 49915 KiB  
Article
A Software Emulator for the Modelling and Control of an Activated Sludge Process in a Wastewater Treatment Plant
by Dan Selișteanu, Ion-Marian Popescu, Monica Roman, Constantin Șulea-Iorgulescu and Sorin Mehedințeanu
Processes 2021, 9(11), 2054; https://0-doi-org.brum.beds.ac.uk/10.3390/pr9112054 - 16 Nov 2021
Cited by 2 | Viewed by 1758
Abstract
The design and implementation of a simulator, as a real-time application, for a complex process from the biological treatment stage of a wastewater treatment plant (WWTP), is addressed. More precisely, this emulator was achieved as a software tool that can be later integrated [...] Read more.
The design and implementation of a simulator, as a real-time application, for a complex process from the biological treatment stage of a wastewater treatment plant (WWTP), is addressed. More precisely, this emulator was achieved as a software tool that can be later integrated into a more complex SCADA (supervisory control and data acquisition) system of the WWTP Făcăi, Romania. The basic idea is to implement and validate a reduced-order model of the activated sludge process (ASP), initially simulated in the Matlab/Simulink environment (The MathWorks, Inc., Natick, MA, USA). Moreover, an advanced multivariable adaptive control scheme of the ASP is addressed. This software tool can be made to work in parallel with the evolution of the process and can have as input signals measured directly at the process level, possibly following parametric or model adaptations. The software emulator is developed in the LabWindows/CVI programming environment (National Instruments), which offers low-level access to hardware or software systems that have minimal open-architecture facilities. This environment provides versatile drivers and software packages that can facilitate the interaction with software tools developed within some earlier SCADA systems. The structure and the graphical interface of the emulator, some functionalities, experiments, and evolution of main variables are presented. Full article
(This article belongs to the Special Issue Contemporary Methods for Process Modelling and Control)
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18 pages, 6665 KiB  
Article
Application of the Modified Fuzzy-PID-Smith Predictive Compensation Algorithm in a pH-Controlled Liquid Fertilizer System
by Yongchao Shan, Lixin Zhang, Xiao Ma, Xue Hu, Zhizheng Hu, He Li, Chanchan Du and Zihao Meng
Processes 2021, 9(9), 1506; https://0-doi-org.brum.beds.ac.uk/10.3390/pr9091506 - 26 Aug 2021
Cited by 8 | Viewed by 1982
Abstract
An appropriate pH value of liquid fertilizer can enable crops to better absorb nutrients from fertilizers. However, the mixed liquid fertilizer with high concentration of liquid fertilizer and irrigation water has a high pH value, which affects the absorption of nutrients by crops. [...] Read more.
An appropriate pH value of liquid fertilizer can enable crops to better absorb nutrients from fertilizers. However, the mixed liquid fertilizer with high concentration of liquid fertilizer and irrigation water has a high pH value, which affects the absorption of nutrients by crops. Therefore, the precise regulation of liquid fertilizer pH value is an important link to realize the integration of water and fertilizer in modern agriculture. Due to pipeline transportation and diffusion of the regulating liquid and liquid fertilizer, the pH value control system has the characteristics of time-varying, non-linear and time-delayed models, and it is difficult for ordinary controllers to accurately control the pH value of liquid fertilizer. Therefore, modern agriculture urgently needs a controller that can adapt to non-linear and uncertain systems. According to the characteristics of the pH regulation process of liquid fertilizer, this study proposes and designs a modified fuzzy-PID-Smith predictive compensation algorithm, which adds the fuzzy-PID algorithm to the predictor of the conventional Smith algorithm to compensate for the error between the actual and theoretical models in order to reduce the decline of control quality caused by the model mismatch to the control system. To verify the practicability and robustness of the algorithm in practical applications, a liquid fertilizer pH value control system with STM32F103ZET6 as the control core was developed. The pH control system with fuzzy-PID and Smith algorithm as controller was used as the control group. The model was simulated and tested under two conditions of exact matching and imprecise matching, and performance tests were carried out under different output flow rates. The results showed that the maximum overshoot of the modified fuzzy-PID-Smith predictive compensation algorithm was significantly less than that of the other two algorithms at different output flow rates, with an average of 0.23%. The average steady-state time of adjusting the pH value of liquid fertilizer from 7.3 to 6.8 was 72 s, which was superior to the 145 s and 3.2% of fuzzy-PID and 130 s and 1.4% of the Smith controller. Full article
(This article belongs to the Special Issue Contemporary Methods for Process Modelling and Control)
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Review

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24 pages, 1586 KiB  
Review
Modeling in Brewing—A Review
by Vesela Shopska, Rositsa Denkova-Kostova and Georgi Kostov
Processes 2022, 10(2), 267; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10020267 - 29 Jan 2022
Cited by 9 | Viewed by 5010
Abstract
Beer production has over a thousand-year tradition, but its development in the present continues with the introduction of new technological and technical solutions. The methods for modeling and optimization in beer production through an applied analytical approach have been discussed in the present [...] Read more.
Beer production has over a thousand-year tradition, but its development in the present continues with the introduction of new technological and technical solutions. The methods for modeling and optimization in beer production through an applied analytical approach have been discussed in the present paper. For this purpose, the parameters that are essential for the main processes in beer production have been considered—development of malt blends, guaranteeing the main brewing characteristics; obtaining wort through the processes of mashing, lautering and boiling of wort; fermentation and maturation of beer. Data on the mathematical dependences used to describe the different stages of beer production (one-factor experiments, modeling of mixtures, experiment planning, description of the kinetics of microbial growth, etc.) and their limits have been presented, and specific research results of various authors teams working in this field have been cited. The independent variables as well as the objective functions for each stage have been defined. Some new trends in the field of beer production have been considered and possible approaches for their modeling and optimization have been highlighted. The paper suggests a generalized approach to describe the main methods of modeling and optimization, which does not depend on the beer type produced. The proposed approaches can be used to model and optimize the production of different beer types, and the conditions for their application should be consistent with the technological regimes used in each case. The approaches for modeling and optimization of the individual processes have been supported by mathematical dependencies most typical for these stages. Depending on the specific regimes and objectives of the study, these dependencies can be adapted and/or combined into more general mathematical models. Some new trends in the field of beer production have been considered and possible approaches for their modeling and optimization have been highlighted. Full article
(This article belongs to the Special Issue Contemporary Methods for Process Modelling and Control)
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19 pages, 1879 KiB  
Review
Model-Based Monitoring of Biotechnological Processes—A Review
by Velislava Lyubenova, Georgi Kostov and Rositsa Denkova-Kostova
Processes 2021, 9(6), 908; https://0-doi-org.brum.beds.ac.uk/10.3390/pr9060908 - 21 May 2021
Cited by 6 | Viewed by 2128
Abstract
The monitoring of the main variables and parameters of biotechnological processes is of key importance for the research and control of the processes, especially in industrial installations, where there is a limited number of measurements. For this reason, many researchers are focusing their [...] Read more.
The monitoring of the main variables and parameters of biotechnological processes is of key importance for the research and control of the processes, especially in industrial installations, where there is a limited number of measurements. For this reason, many researchers are focusing their efforts on developing appropriate algorithms (software sensors (SS)) to provide reliable information on unmeasurable variables and parameters, based on the available on-line information. In the literature, a large number of developments related to this topic that concern data-based and model-based sensors are presented. Up-to-date reviews of data-driven SS for biotechnological processes have already been presented in the scientific literature. Hybrid software sensors as a combination between the abovementioned ones are under development. This gives a reason for the article to be focused on a review of model-based software sensors for biotechnological processes. The most applied model-based methods for monitoring the kinetics and state variables of these processes are analyzed and compared. The following software sensors are considered: Kalman filters, methods based on estimators and observers of a deterministic type, probability observers, high-gain observers, sliding mode observers, adaptive observers, etc. The comparison is made in terms of their stability and number of tuning parameters. Particular attention is paid to the approach of the general dynamic model. The main characteristics of the classic variant proposed by D. Dochain are summarized. Results related to the development of this approach are analyzed. A key point is the presentation of new formalizations of kinetics and the design of new algorithms for its estimation in cases of uncertainty. The efficiency and applicability of the considered software sensors are discussed. Full article
(This article belongs to the Special Issue Contemporary Methods for Process Modelling and Control)
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