Ali Deeb

@spbstu.ru

School of Cyber-physical Systems and Control, Institute of Computer Science and Cyber Security
SPbPU

Ali Deeb


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https://researchid.co/ali0deeb

RESEARCH, TEACHING, or OTHER INTERESTS

Control and Systems Engineering
9

Scopus Publications

27

Scholar Citations

3

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • Hierarchical Multi-objective Control of Nonlinear Systems with Dynamical Input Constraints
    Ali Deeb, Vladimir Khokhlovskiy, Viacheslav Shkodyrev
    Artificial Intelligence and Applications, 2026
    This work presents a multi-level hierarchical control strategy to address the problem of complex multi-objective optimization-based control in real time. Our suggested strategy utilizes evolutionary algorithms to solve the high-level optimization problem, providing a control policy under which a lower-level control loop handles the dynamics of the control values while respecting both regional and dynamical input constraints. Moreover, a real-time under-policy prediction phase is developed to absorb the latency of the computationally expensive policy search phase. The overall strategy is designed to leverage nonlinear systems without the need for further linearization or operating point approximations. Experimental results on a drum boiler-turbine unit simulation demonstrate the capabilities of our suggested strategy to steer the system outputs toward desired values with faster convergence compared to traditional methods. The proposed approach shows significant improvements in control performance, handling complex nonlinear control problems in real time, and providing optimized and fast control signals to guide the system outputs towards different operating points. Received: 10 September 2024 | Revised: 8 February 2025 | Accepted: 24 February 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data sharing is not applicable to this article as no new data were created or analyzed in this study. Author Contribution Statement Ali Deeb: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization. Vladimir Khokhlovskiy: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Writing – original draft, Writing – review & editing, Visualization, Supervision. Viacheslav Shkodyrev: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration.
  • ENHANCING EVOLUTIONARY CONTROLLERS WITH A REJECTION-BASED GENETIC ALGORITHM
    igher School of Cyberphysical Systems, Control, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russian Federation, Ali Deeb, Vladimir Khokhlovskiy, igher School of Cyberphysical Systems, Control, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russian Federation, Viacheslav Shkodyrev, igher School of Cyberphysical Systems, Control, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russian Federation
    Cybernetics and Physics, 2025
    Genetic Algorithms (GAs) are promising for receding-horizon control in nonlinear, constrained systems, but their wall-clock cost is dominated by objective evaluations. We propose a rejection-based GA tailored to horizon-structured genomes that performs exactly one plant-evaluation batch per generation and filters unevaluated offspring through a lightweight, calibrated classifier. On a standard nonisothermal Continuous Stirred Tank Reactor (CSTR) benchmark, we compare four optimizers under identical settings: a baseline GA, our committee-gated RB-GA, the baseline with Simple Variable Population Sizing (SVPS), and the recently proposed Two-Level Adaptive Simulated Binary Crossover (TLASBX). RB-GA consistently improves tracking accuracy over the baseline at lower generation budgets. Baseline+SVPS and TLASBX closely match the baseline. We attribute this outcome to the limited number of generations, which constrains their learning effects. Overall, the results indicate that the proposed mechanism enhances optimization convergence in expensive-evaluation regimes.
  • Adaptive Simulated Binary Crossover with Bayesian Optimization for Industrial Applications
    Ali Deeb, Vladimir Khokhlovskiy, Viacheslav Shkodyrev
    Proceedings 2025 International Russian Smart Industry Conference Smartindustrycon 2025, 2025
    Genetic Algorithms are widely used as global optimization solvers for complex and non-convex problems in industrial applications (resource and load planning, workshop logistics, process control, etc.). Simulated Binary Crossover (SBX) is a common operator in real-coded Genetic Algorithms for continuous optimization, but it typically relies on a fixed distribution index parameter that may not stay optimal throughout the evolutionary process. To address this, we propose a Transfer Learning-Based Adaptive Simulated Binary Crossover approach, which employs Bayesian Optimization to dynamically update the parameter during the Genetic Algorithm run. The parameter is periodically re-optimized based on the population's current dynamics. Tested on benchmark functions including Rosenbrock, Rastrigin, Ackley, and Griewank, our method achieves faster convergence and higher solution quality than standard Genetic Algorithms with a fixed parameter.
  • Ontology-Driven Semantic Interoperability for Discrete Manufacturing
    Vladimir Khokhlovskiy, Ali Deeb, Ivan A. Skoglikov, Nikita A. Vedmed
    Proceedings 2025 International Russian Smart Industry Conference Smartindustrycon 2025, 2025
    The paper proposes ontologies for planning assembly production and mechanical processing to support decision-making in managing a discrete manufacturing process. To obtain a complete picture of the technological process, it is necessary to ensure the systematic integration of all relevant data from several systems and devices based on knowledge of the production area. Semantic interoperability is ensured based on the implementation of the same ontology in interacting systems. The ontologies were created in the open Protégé system to establish correspondence between product manufacturing concepts when processing a knowledge base by translating data from the MES (Manufacturing Execution System) and the RDF file (Resource Description Framework). The architecture of the system using the knowledge base is proposed. An application in C# is considered, which is included in the system, reads operational values of technology implementation parameters and forms new triplets in the knowledge base. The difference of the proposed approach is, firstly, the ontological integration of assembly production and mechanical processing and, secondly, the consideration of operationally changing data transferred from the DBMS to the KBMS to support decision-making. The time of information transfer to the knowledge base and to the database were obtained; a comparison of average recording times is given. The created application and the developed ontologies can become the basis for creating digital twins for the discrete production process
  • Ontology-Based Decision Support for Boiler Operation
    Vladimir Khokhlovskiy, Evgeniy Borisov, Ali Deeb, Iliya Orlov
    Proceedings 2025 International Conference on Industrial Engineering Applications and Manufacturing Icieam 2025, 2025
    The paper is devoted to the use of ontology-based decision support to improve the efficiency of boiler operation. One of the ways to solve the problem is the implementation of a common semantic model that will standardize the semantic properties of data for the systems under consideration in a specific subject area. This model can be created using semantic technologies that unify the meaning, content and format of data. The paper considers the theoretical aspects and practical implementation of the concept of decision support based on use of knowledge base with real-time synchronization providing semantic interoperability for systematization and formalization of an area related to a boiler unit in an intelligent control system. For the first time (according to available sources), an ontology of a boiler unit is proposed, developed in the open Protégé system and describing its structure, classes, relations and other components. A <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{C} \#$</tex> application demonstrates the ability to form relations with nonstandard content (for example, expressed as a triple “«Percentage of continuous boiler blowdown» «Affects the consumption of superheated steam with a delay» of 5.0 minutes”), which is a distinctive feature of the proposed approach. The knowledge base obtained as a result of the application's operation represents a formal description of the boiler unit and can be used for predictive analytics and in decision support systems.
  • Model Predictive Control and Genetic Algorithms for Optimization of Continuous Stirred Tank Reactors
    Ali Deeb, Vladimir N. Khokhlovskiy, Viacheslav P. Shkodyrev
    Studies in Systems Decision and Control, 2024
  • Optimal Path-Following Control for Redundant Manipulators: A Multi-Objective Optimization Approach
    Ali Deeb, Ammar Aakel, Vladimir Khokhlovskiy, Viacheslav Shkodyrev
    Advances in Transdisciplinary Engineering, 2024
    This paper presents an optimal control framework tailored for redundant robotic manipulators, aiming to devise precise joint-space trajectories while minimizing control efforts. The core contribution is the formulation of trajectory planning as a multi-objective optimization problem, tackled through a Genetic Algorithm-based Model Predictive Control strategy, followed by Gradient Descent refinement. Moreover, we develop a strategy to apply the resulted high-level design of the joint-space trajectory into a dynamic time-series control strategy that respects the physical constraints of actuators in motion, speed, acceleration and jerk. Experimental results on a simulation model underscore the framework’s efficacy, demonstrating minimal positioning errors without the need for high computational resources for the trajectory design. Moreover, dynamical analysis of the actuators signals for the low-level phase demonstrates the ability of the overall framework to be applied on a real robotic manipulator.
  • Optimizing Multi-Level Industrial Systems through Archive-Based Data-Driven Configuration
    Ali Deeb, Vladimir Khokhlovskiy, Victor Prokofiev, Viacheslav Shkodyrev
    Rusautocon Proceedings of the International Russian Automation Conference, 2024
    The paper presents a refined methodology for multi-criteria optimization of hierarchical production processes, leveraging Pareto-front analysis through non-dominated sorting. The proposed approach is aimed at increasing the efficiency of the system by considering mutually conflicting objective functions to guide the selection of configuration parameters towards maximizing the possibility of having future values of these objective functions lie on the Pareto front. An example of a boiler unit of a Combined Heat and Power plant (CHP) is considered, and a corresponding hierarchical boiler model is built and investigated with use of historical data. As an example of objective functions, the efficiency of the boiler unit and the consumption of overheated steam are considered. Moreover, the paper examines two definitions of the concept “hierarchy” and demonstrates their practical application, based on the data overflow through the multi-level model of the control object. Our proposed methodology applies a top-to-down non-dominated sorting algorithm through a quantized version of the data, for determining the optimal configuration parameters across different levels of a system's hierarchy. Our findings show the perspectives of updating the different setups of a system's configuration parameters according to the desired region of work, to optimize the overall possible outcome.
  • COVID-19 diagnosis with Deep Learning: Adjacent-pooling CTScan-COVID-19 Classifier Based on ResNet and CBAM
    Ali Deeb, Ahmad Debow, Saleem Mansour, Viacheslav Shkodyrev
    Biomedical Signal Processing and Control, 2023

RECENT SCHOLAR PUBLICATIONS

  • Ontology-Based Decision Support for Boiler Operation
    V Khokhlovskiy, E Borisov, A Deeb, I Orlov
    2025 International Conference on Industrial Engineering, Applications and … , 2025
    2025.0
  • Ontology-Driven Semantic Interoperability for Discrete Manufacturing
    V Khokhlovskiy, A Deeb, IA Skoglikov, NA Vedmed
    2025 International Russian Smart Industry Conference (SmartIndustryCon), 953-959 , 2025
    2025.0
  • Adaptive Simulated Binary Crossover with Bayesian Optimization for Industrial Applications
    A Deeb, V Khokhlovskiy, V Shkodyrev
    2025 International Russian Smart Industry Conference (SmartIndustryCon), 608-613 , 2025
    2025.0
    Citations: 2
  • Hierarchical Multi-objective Control of Nonlinear Systems with Dynamical Input Constraints
    A Deeb, V Khokhlovskiy, V Shkodyrev
    Artificial Intelligence and Applications , 2025
    2025.0
    Citations: 1
  • Optimizing Multi-Level Industrial Systems through Archive-Based Data-Driven Configuration
    A Deeb, V Khokhlovskiy, V Prokofiev, V Shkodyrev
    2024 International Russian Automation Conference (RusAutoCon), 252-259 , 2024
    2024.0
    Citations: 1
  • Model predictive control and genetic algorithms for optimization of continuous stirred tank reactors
    A Deeb, VN Khokhlovskiy, VP Shkodyrev
    Smart Electromechanical Systems: Mathematical and Software Engineering, 185-191 , 2024
    2024.0
    Citations: 6
  • Intelligent knowledge-based control system of industrial steam boiler: выпускная квалификационная работа магистра: направление 09.04. 01 «Информатика и вычислительная техника …
    А Диб
    2024.0
  • Интерактивное взаимодействие с пользователем в иерархической производственной системе поддержки принятия решений
    Д Али, АТ Маликов, ВН Хохловский
    Системный анализ в проектировании и управлении 28 (2), 489-494 , 2024
    2024.0
  • Анализ рынка систем диспетчерского управления технологическими процессами и сбором данных (SCADA-систем) в рамках направления «Технет» НТИ. Экспертно-аналитический доклад
    АИ Боровков, ОИ Рождественский, ЕИ Павлова, ИИ Поняева, ...
    2024.0
  • Анализ рынка систем управления производством (MES-систем) в рамках направления «Технет» НТИ. Экспертно-аналитический доклад
    АИ Боровков, ОИ Рождественский, ЕИ Павлова, ИИ Поняева, ...
    2024.0
    Citations: 1
  • Диагностирование асинхронного двигателя с помощью деревьев решений по имитационной модели
    КА Виноградчий, Д Али, ЮН Кожубаев, ВН Хохловский
    Системный анализ в проектировании и управлении 28 (2), 533-541 , 2024
    2024.0
  • Имитационное моделирование для решения задачи динамической эколого-экономической диспетчеризации
    Д Али, ИВ Орлов, СА Скороварова, ВН Хохловский
    Системный анализ в проектировании и управлении 28 (2), 113-119 , 2024
    2024.0
  • Optimal path-following control for redundant manipulators: A multi-objective optimization approach
    A Deeb, A Aakel, V Khokhlovskiy, V Shkodyrev
    Mechatronics and Automation Technology: Proceedings of the 3rd International … , 2024
    2024.0
    Citations: 3
  • Covid-19 diagnosis with deep learning: adjacent-pooling ctscan-Covid-19 classifier based on resnet and cbam
    A Deeb, A Debow, S Mansour, V Shkodyrev
    Biomedical Signal Processing and Control 86, 105285 , 2023
    2023.0
    Citations: 13
  • ENHANCING EVOLUTIONARY CONTROLLERS WITH A REJECTION-BASED GENETIC ALGORITHM
    A Deeb, V Khokhlovskiy, V Shkodyrev

MOST CITED SCHOLAR PUBLICATIONS

  • Covid-19 diagnosis with deep learning: adjacent-pooling ctscan-Covid-19 classifier based on resnet and cbam
    A Deeb, A Debow, S Mansour, V Shkodyrev
    Biomedical Signal Processing and Control 86, 105285 , 2023
    2023.0
    Citations: 13
  • Model predictive control and genetic algorithms for optimization of continuous stirred tank reactors
    A Deeb, VN Khokhlovskiy, VP Shkodyrev
    Smart Electromechanical Systems: Mathematical and Software Engineering, 185-191 , 2024
    2024.0
    Citations: 6
  • Optimal path-following control for redundant manipulators: A multi-objective optimization approach
    A Deeb, A Aakel, V Khokhlovskiy, V Shkodyrev
    Mechatronics and Automation Technology: Proceedings of the 3rd International … , 2024
    2024.0
    Citations: 3
  • Adaptive Simulated Binary Crossover with Bayesian Optimization for Industrial Applications
    A Deeb, V Khokhlovskiy, V Shkodyrev
    2025 International Russian Smart Industry Conference (SmartIndustryCon), 608-613 , 2025
    2025.0
    Citations: 2
  • Hierarchical Multi-objective Control of Nonlinear Systems with Dynamical Input Constraints
    A Deeb, V Khokhlovskiy, V Shkodyrev
    Artificial Intelligence and Applications , 2025
    2025.0
    Citations: 1
  • Optimizing Multi-Level Industrial Systems through Archive-Based Data-Driven Configuration
    A Deeb, V Khokhlovskiy, V Prokofiev, V Shkodyrev
    2024 International Russian Automation Conference (RusAutoCon), 252-259 , 2024
    2024.0
    Citations: 1
  • Анализ рынка систем управления производством (MES-систем) в рамках направления «Технет» НТИ. Экспертно-аналитический доклад
    АИ Боровков, ОИ Рождественский, ЕИ Павлова, ИИ Поняева, ...
    2024.0
    Citations: 1
  • Ontology-Based Decision Support for Boiler Operation
    V Khokhlovskiy, E Borisov, A Deeb, I Orlov
    2025 International Conference on Industrial Engineering, Applications and … , 2025
    2025.0
  • Ontology-Driven Semantic Interoperability for Discrete Manufacturing
    V Khokhlovskiy, A Deeb, IA Skoglikov, NA Vedmed
    2025 International Russian Smart Industry Conference (SmartIndustryCon), 953-959 , 2025
    2025.0
  • Intelligent knowledge-based control system of industrial steam boiler: выпускная квалификационная работа магистра: направление 09.04. 01 «Информатика и вычислительная техника …
    А Диб
    2024.0
  • Интерактивное взаимодействие с пользователем в иерархической производственной системе поддержки принятия решений
    Д Али, АТ Маликов, ВН Хохловский
    Системный анализ в проектировании и управлении 28 (2), 489-494 , 2024
    2024.0
  • Анализ рынка систем диспетчерского управления технологическими процессами и сбором данных (SCADA-систем) в рамках направления «Технет» НТИ. Экспертно-аналитический доклад
    АИ Боровков, ОИ Рождественский, ЕИ Павлова, ИИ Поняева, ...
    2024.0
  • Диагностирование асинхронного двигателя с помощью деревьев решений по имитационной модели
    КА Виноградчий, Д Али, ЮН Кожубаев, ВН Хохловский
    Системный анализ в проектировании и управлении 28 (2), 533-541 , 2024
    2024.0
  • Имитационное моделирование для решения задачи динамической эколого-экономической диспетчеризации
    Д Али, ИВ Орлов, СА Скороварова, ВН Хохловский
    Системный анализ в проектировании и управлении 28 (2), 113-119 , 2024
    2024.0
  • ENHANCING EVOLUTIONARY CONTROLLERS WITH A REJECTION-BASED GENETIC ALGORITHM
    A Deeb, V Khokhlovskiy, V Shkodyrev