Applied sciences

Archives of Control Sciences

Description

Archives of Control Sciences welcomes for consideration papers on topics of significance in broadly understood control science and related areas, including: basic control theory, optimal control, optimization methods, control of complex systems, mathematical modeling of dynamic and control systems, expert and decision support systems and diverse methods of knowledge modelling and representing uncertainty (by stochastic, set-valued, fuzzy or rough set methods, etc.), robotics and flexible manufacturing systems. Related areas that are covered include information technology, parallel and distributed computations, neural networks and mathematical biomedicine, mathematical economics, applied game theory, financial engineering, business informatics and other similar fields.

Aims and Scope: Archives of Control Sciences publishes papers in the broadly understood field of control science and related areas while promoting the closer integration of the Polish, as well as other Central and East European scientific communities with the international world of science.

IMPACT FACTOR 2022: 1.2

CiteScore 2022: 2.7

SCImago Journal Rank (SJR) 2022: 0.304

Source Normalized Impact per Paper (SNIP) 2021: 0.570

ISSN

ISSN 1230-2384

Publishers

Committee of Automatic Control and Robotics PAS

Editor-in-Chief

prof. dr hab. inż. Marek Pawełczyk

Deputy/ Managing Editor

dr hab. inż. Dariusz Bismor

Department of Measurements and Control Systems

Silesian University of Technology, Gliwice, Poland

Editorial Advisory Board
Sebastian Anita, University Alexandru Ioan Cuza, Romania
Roman Barták, Charles University, Prague, Czech Republic
Andrzej Bartoszewicz, Lodz University of Technology, Poland
Jacek Błażewicz, Poznań University of Technology, Poland
Adam Czornik, Silesian University of Technology, Poland
Reggie Davidrajuh, University of Stavanger, Norway
Moritz Diehl, University of Freiburg, Germany
Marcelo D.Fragoso, LNCC/MCT, Rio de Janeiro, Brasil
Avner Friedman, MBI Ohio State University, Columbus, USA
Mats Gyllenberg, University of Helsinki, Finland
Wassim M. Haddad, Georigia University, Atlanta, USA
Alberto Isidori, Università di Roma "La Sapienza" Italia
Asatur Zh. Khurshudyan, NAS of Armenia, Armenia
Marek Kimmel, Rice University Houston, USA
Jerzy Klamka, Institute of Theoretical and Applied Informatics PAS, Poland
Józef Korbicz, University of Zielona Góra, Poland
Piotr Kulczycki, Institute of System Research PAS, Poland
Irena Lasiecka, University of Virginia, USA
Urszula Ledzewicz, Southern Illinois University at Edwardsville, USA
Magdi S. Mahmoud, KFUM, Dahram, Saudi Arabia
Evgenii K. Makarov, NAS of Belarus, Belarus
Krzysztof Malinowski, Warsaw University of Technology, Poland
Wojciech Mitkowski, AGH University of Science and Technology, Poland
Francisco Javier Muros, University of Seville, Spain
Bozenna Pasik-Duncan, University of Kansas, Lawrence, USA
Marek Pawełczyk, Silesian University of Technology, Poland
Ian Postlethwaite, Newcastle University, Newcastle, UK
Witold Respondek, Institut National des Sciences Appliquées de Rouen, France
Eric Rogers, University of Southampton, UK
Heinz Schaettler, Washington University, St Louis, USA
Ryszard Tadeusiewicz, AGH University of Science and Technology, Poland
Jan Węglarz, Poznań University of Technology, Poland
Liu Yungang, Shandong University, PRC
Valery D. Yurkevich, Novosibirsk State Technical University, Russia

Institute of Automatic Control
Silesian University of Technology
Akademicka 16
44-101 Gliwice, Poland

acs@polsl.pl
http://acs.polsl.pl/

Archives of Control Sciences is an open access journal with all content available with no charge in full text version.

The journal content is available under the licencse CC BY-NC-ND 4.0 https://creativecommons.org/licenses/by-nc-nd/4.0/.

Volumes
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Content

Archives of Control Sciences | 2026 | vol. 36 | No 1

1 Game theoretic approach for energy scheduling in demand side management for smart grid applications

Murugeswari Palanisamy , Amalorpava Mary Rajee Samuel , Yamuna Devi Manickam.Malu , Priya Baldoss

Archives of Control Sciences | 2026 | vol. 36 | No 1 | 1-21 | DOI: 10.24425/acs.2026.158419

Keywords: game theoretic demand response algorithm energy scheduling energy consumption load pricing schemes

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Abstract

The emergence of Game theory (GT) enabled with demand side management (DSM) has the applications in the field of smart grid applications. A mathematical method called game theory uses desirable rules to identify the circumstances under which all actors can win. Various agents can be used to optimize their gains. In terms of customer utility, demand response algorithms are categorized as agents in terms of customer utility. A centralized demand response (DR) scheduling algorithm that meets the varied energy consumption needs of a community can be difficult owing to the differences among residents. A non-cooperative DR-GT model is proposed to improve individual benefits in the energy consumption scheduling algorithm. The appliance information comprises different power levels to categorize the residents, which reduces the scheduling traffic between the residents and aggregator. There is a 23% reduction in the peak-to average ratio and increase in renewable energy usage by 13–25%, as better scheduling based on the flexibility of consumer loads and pricing schemes. Smart grid efficiency is improved by 23–30%, owing to reduced energy losses, fewer system imbalances, and lower wears on grid infrastructure.

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Authors and Affiliations

Murugeswari Palanisamy

e-mail:

ORCID:

Amalorpava Mary Rajee Samuel

e-mail:

ORCID:

Yamuna Devi Manickam.Malu

Priya Baldoss

e-mail:

ORCID:

Department of Electronics and Communication Engineering, Sethu Institute of Technology Kariapatti-626 115,TN, India
Department of Electricaland Information Engineering, University of Witwatersrand, Johannesburg, South Africa
Department of Computer Science and Engineering, Koneru LakshmaiahEducation Foundation, Vĳayawada, AP, India
Department of CSE, Sri Sairam Engineering College, Chennai, India

2 A new 4-D hyperchaotic Lü system with a curve equilibrium, its bifurcation analysis, multistability, circuit simulation and synchronization via integral sliding mode control

Sundarapandian Vaidyanathan , Fareh Hannachi , Irene M. Moroz , Mohamad Afendee Mohamed , Aceng Sambas , R. Bullibabu

Archives of Control Sciences | 2026 | vol. 36 | No 1 | 23-54 | DOI: 10.24425/acs.2026.158420

Keywords: chaos chaotic systems curve equilibrium bifurcation multistability circuit design synchronization sliding mode control

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Abstract

In this research work, we first obtain a new 3-D chaotic Lü system by modifying the dynamics of the classical Lü chaotic system (2002). Next, by introducing a state feedback to the new 3-D modified Lü chaotic system, we obtain a new 4-D hyperchaotic Lü system with a curve equilibrium.We carry out a detailed bifurcation analysis of the new4-D hyperchaotic system with a curve equilibrium and describe the bifurcation transition diagrams and Lyapunov exponents diagrams.We also derive new multistability results of the new 4-D hyperchaotic Lü system with a curve equilibrium. For engineering applications, we provide an electronic circuit simulation of the proposed hyperchaotic Lü system using MultiSim 14.0. As a control application, we derive new results for the complete synchronization for a pair of new hyperchaotic Lü systems taken as the master and slave systems. We have used integral sliding mode control for the derivation of the synchronizing control law for the complete synchronization design for the new hyperchaotic Lü system. MATLAB simulations are provided to illustrate the main results of this research work.

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Authors and Affiliations

Sundarapandian Vaidyanathan

e-mail:

ORCID:

Fareh Hannachi

e-mail:

ORCID:

Irene M. Moroz

e-mail:

ORCID:

Mohamad Afendee Mohamed

e-mail:

ORCID:

Aceng Sambas

e-mail:

ORCID:

R. Bullibabu

Centre for Control Systems, Vel Tech University, 400 Feet Outer Ring Road, Avadi, Chennai-600062 Tamil Nadu, India andFaculty of Information and Computing, Universiti Sultan Zainal Abidin Terengganu, Malaysia
Department of Management Sciences,Echahid Cheikh Larbi Tebessi University, Route de Constantine, 12022, Tebessa, Algeria
Mathematical Institute, University of Oxford, Andrew Wiles Building, ROQ, Oxford Ox2 6GG, UK
Faculty of Information and Computing, Universiti Sultan Zainal Abidin, Terengganu, Malaysia
Faculty of Informaticsand Computing, Universiti Sultan ZainalAbidin, Gong Badak, 21300, Terengganu, Malaysia and Departmentof Mechanical Engineering, Universitas Muhammadiyah Tasikmalaya, Jawa Barat 46196, Indonesia
Department of Artificial Intelligence, Machine Learning and Data Science, KITS Akshar Institute of Technology, NH-16, Yanamadala, Guntur-522019, Andhra Pradesh, India

3 AI-driven big data visualization for cybersecurity using bipolar fuzzy Einstein prioritized operators

Ubaid ur Rehman , Tahir Mahmood , Hafiz Muhammad Waqas , Abaid ur Rehman Virk

Archives of Control Sciences | 2026 | vol. 36 | No 1 | 55-84 | DOI: 10.24425/acs.2026.158421

Keywords: optimization models control problem efficient solution

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Abstract

As cyberattacks become more advanced, advanced AI-based big data visualization is now needed for effective threat detection. Yet, choosing the best visualization tools is some multicriteria decision-making (MCDM) task that involves considering many criteria containing both positive and negative aspects. WhileMCDMmethods that address the selection and classification of AI-driven big data visualization tools focus on the positive aspects of the evaluation criteria and ignore the negative aspects of the criteria, resulting in incomplete evaluations. Further, although Einstein operators have shown strong results in uncertain and imprecise situations and MCDM approaches, they have not yet been used in bipolar fuzzy frameworks, which leaves a major gap in decision-making methods. To overcome these problems, this article interprets a bipolar fuzzy MCDM methodology based on Einstein prioritized operators to systematically evaluate and classify AI-driven big data visualization tools for cybersecurity threat detection. For this method, Einstein prioritized operators within a bipolar fuzzy framework devised in this article, which can aggregate both positive and negative aspects of the criteria.Acomprehensive case study is shown to assess and classify the prominent AI-driven big data visualization tools for cybersecurity threat detection, considering critical criteria with dual aspects. The proposed methodology is meticulously compared with the prevailing MCDM methods to validate its dominance in handling uncertainty and the bipolarity of the criteria. This article helps security professionals choose the right AI-powered visualization tools which, in turn improve the cybersecurity of their organizations and make it easier to detect threats.

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Authors and Affiliations

Ubaid ur Rehman

e-mail:

ORCID:

Tahir Mahmood

e-mail:

ORCID:

Hafiz Muhammad Waqas

e-mail:

ORCID:

Abaid ur Rehman Virk

e-mail:

ORCID:

Department of Mathematics, University of Management and Technology, C-II, Johar Town, Lahore, 54700, Punjab, Pakistan
Department of Mathematics and Statistics, International Islamic University Islamabad, Islamabad 44000, Pakistan

4 Practical aspects of fast matrix multiplication

Marek Kubale , Damian Niemczyk

Archives of Control Sciences | 2026 | vol. 36 | No 1 | 85-98 | DOI: 10.24425/acs.2026.158422

Keywords: AlphaTensor computational complexity fast matrix multiplication linear algebra

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Abstract

The aim of this paper is to analyze the development of algorithms for Fast Matrix Multiplication (FMM) in both historical and technical contexts, as well as to compare available solutions on consumer-grade computer hardware. We review advancements in estimating the theoretical computational complexity of FMM and optimization techniques that are used in widely adopted algorithms, with a particular focus on optimal cache memory usage and leveraging Graphics Processing Units (GPU). The methodology of tests and their analysis highlight the performance differences of the considered algorithms depending on the matrix size and the nature of the data stored in them. Results indicate the significant role of tailoring the chosen algorithm to the available hardware and the specific application in which the algorithm is being performed. Also, we emphasize that the FMM algorithms can be applied not only to linear algebra problems but also to current problems in science and engineering, such as artificial intelligence, databases, parallel computations, computational biology, pattern recognition, and compiler construction, to mention just a few examples.

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Authors and Affiliations

Marek Kubale

e-mail: kubale@pg.edu.pl

ORCID:

Damian Niemczyk

Gdynia Maritime University, Faculty of Computer Science, Gdynia, Poland
Gdańsk University of Technology, Facultyof Electronics, Telecommunications and Informatics, Gdańsk, Poland

5 Computational framework for dynamic cardiovascular risk assessment with cluster-specific Cox models and cumulative risk analysis

Himanshi Liyanage , Marta Lipnicka

Archives of Control Sciences | 2026 | vol. 36 | No 1 | 99-131 | DOI: 10.24425/acs.2026.158423

Keywords: cardiovascular disease cox proportional hazards model independent hazard functions competitive learning cluster-based data simplification cumulative prevalence ratio personalized risk assessment

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Abstract

This paper presents a novel computational framework for assessing cardiovascular disease (CVD) risk by integrating unsupervised clustering techniques with survival analysis. The proposed method enables dynamic and individualized risk prediction by organizing patient data into structured clusters based on shared cardiovascular risk factors. The framework begins with competitive learning, an unsupervised clustering method, to group patients into clusters that reflect distinct risk profiles. Each cluster is represented by its centroid, calculated as the mean of the 9-dimensional feature vectors of its members, ensuring that the clusters effectively summarize patient data while preserving critical risk characteristics. For each cluster, an independent Cox Proportional Hazards Model is applied to analyze survival data, capturing the unique relationships between cardiovascular risk factors and survival outcomes within that cluster. A key innovation of this study is the introduction of the Cumulative Prevalence Ratio (CPR), a new metric that aggregates hazard rates over time separately for each cluster. This approach provides a comprehensive view of cumulative cardiovascular risk, enabling precise categorization of the patient into risk groups based on cumulative exposure to evolving risk factors. By integrating cluster-specific hazard functions and temporal risk metrics, the proposed framework improves the precision and adaptability of CVD risk predictions, paving the way for personalized and data-driven healthcare interventions.

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Authors and Affiliations

Himanshi Liyanage

e-mail:

ORCID:

Marta Lipnicka

e-mail:

ORCID:

Faculty of Mathematics and Computer Science, University of Lodz, Stefana Banacha 22, 90-238 Łódź, Poland

6 Reinforcement learning-based obstacle avoidance for continuum robots

Jakub Kołota , Turhan Can Kargin

Archives of Control Sciences | 2026 | vol. 36 | No 1 | 133–158 | DOI: 10.24425/acs.2026.158424

Keywords: reinforcement learning DDPG continuum robots

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Abstract

This work presents a reinforcement learning framework for controlling a planar threesection continuum robot in environments with static obstacles. Assuming constant curvature for each section, the robot is trained to navigate toward a fixed goal while avoiding collisions with multiple static objects. A custom simulation environment was developed to support three levels of scenario difficulty, easy, medium and hard, each with varying obstacle density and placement. The learning process is driven by the Deep Deterministic Policy Gradient (DDPG) algorithm, which enables smooth and continuous curvature control. Careful attention was paid to the design of the reward function and the network architecture, both of which were critical to achieving stable and reliable policy learning. Performance was evaluated across multiple runs, revealing that the agent successfully generalized its behavior across scenarios of increasing complexity. The proposed framework demonstrates the potential of reinforcement learning as a viable approach to safe and adaptive control in continuum robotic systems, with promising implications for applications such as medical navigation, search and rescue, and inspection in confined environments.

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Authors and Affiliations

Jakub Kołota

e-mail:

ORCID:

Turhan Can Kargin

e-mail:

ORCID:

Institute of Automatic Control and Robotics, Poznan University of Technology, Piotrowo 3A, 60-965 Poznań, Poland
unafiliated, Izmir, Turkey

7 Asymptotic behavior of nonlinear systems with impulses: Application to Hopfield neural networks

Wided Gouadri , Mohamed Ali Hammami

Archives of Control Sciences | 2026 | vol. 36 | No 1 | 159-179 | DOI: 10.24425/acs.2026.158425

Keywords: nonlinear systems impulsive perturbation asymptotic stability practical exponential stability Gronwall-Bellman inequality

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Abstract

In this paper, we provide some sufficient conditions for the exponential stability of solutions of nonlinear impulsive differential systems by using some inequality of Gronwall-Bellman type. Practical exponential stability is also investigated for a class of perturbed impulsive systems. Several numerical examples are provided to demonstrate the effectiveness of the theoretical results. Furthermore, Hopfield neural networks system is discussed as an application.

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Authors and Affiliations

Wided Gouadri

e-mail:

ORCID:

Mohamed Ali Hammami

e-mail:

ORCID:

Laboratory Stability and Control of Systems and NonlinearPDEs, University of Sfax, Faculty of Sciences of Sfax, Tunisia

8 Invariant properties of positive linear systems with integer and fractional orders

Tadeusz Kaczorek

Archives of Control Sciences | 2026 | vol. 36 | No 1 | 181–194 | DOI: 10.24425/acs.2026.158426

Keywords: invariance positive linear system stability reachability observability transfer matrix

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Abstract

The invariant properties of the stability, reachability, observability and transfer matrices of positive linear continuous-time systems with integer and fractional orders are investigated. It is shown that the stability, reachability, observability and transfer matrix of positive linear systems are invariant under their integer and fractional orders.

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Authors and Affiliations

Tadeusz Kaczorek

e-mail:

ORCID:

Faculty of Electrical Engineering, Bialystok University of Technology, Wiejska 45D, 15-351 Białystok, Poland

9 On the transformation of FOTF system to fractional order LTI model

Jacek Jagodziński , Marta Lampasiak

Archives of Control Sciences | 2026 | vol. 36 | No 1 | 195-215 | DOI: 10.24425/acs.2026.158427

Keywords: fractional order system fractional order transfer function FOTF fractional orderLTI system model transformation

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Abstract

This article addresses modeling systems using fractional order derivatives, highlighting three basic approaches: differential equations, operator methods, and state space representations. Each approach carries different advantages and limitations in the context of time invariant linear systems (LTI) of fractional order. The focus of the article is on Fractional Order Transfer Functions, which represent a special subject of interest because they offer practical utility with available simulation libraries (e.g., CRONE, FOMCON, NiNteger) and approximation techniques (e.g., Oustaloup, CFE, Thiele, Padé). This paper describes a transition between fractional order transfer functions (FOTF) and pseudo-rational representations of such systems. While the existing literature contains the basics of fractional differential equations and operator theory, it often omits explicit formulas for conversion between different representations. The paper fills a significant gap by proposing a novel algorithm for converting FOTF models to fractional LTI representations. Unlike previous works that implicitly assume such transitions exist, this paper provides formulas for coefficient transformations and demonstrates its effectiveness by minimizing the degree of the system.

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Authors and Affiliations

Jacek Jagodziński

e-mail:

ORCID:

Marta Lampasiak

e-mail:

ORCID:

Faculty of Information and Communication Technology, Department of Control and Quantum Computing, Wrocław University of Science and Technology, Wrocław, Poland

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R. E. Kalman: Mathematical description of linear dynamical system. SIAM J. Control. 1(2), (1963), 152-192.
F. C. Shweppe: Uncertain dynamic systems. Prentice-Hall, Englewood Cliffs, N.J. 1970.

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