<?xml version="1.0" encoding="utf-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "https://jats.nlm.nih.gov/publishing/1.3/JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xml:lang="en">
  <front xmlns:xlink="http://www.w3.org/1999/xlink">
    <journal-meta>
      <journal-title-group>
        <journal-title>Computing, Telecommunication and Control</journal-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Информатика, телекоммуникации и управление</trans-title>
        </trans-title-group>
      </journal-title-group>
      <issn pub-type="epub">2687-0517</issn>
    </journal-meta>
    <article-meta xmlns:xlink="http://www.w3.org/1999/xlink">
      <article-id pub-id-type="publisher-id">10</article-id>
      <article-id pub-id-type="doi">10.18721/JCSTCS.19210</article-id>
      <title-group>
        <article-title>Adaptive weight adjustment in multicriteria control of nonlinear systems based on a Lyapunov function</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Адаптивная настройка весов в задаче многокритериального управления нелинейными системами с использованием функции Ляпунова</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Fershtadt</surname>
            <given-names>Mikhail</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <email>tral1930@mail.ru</email>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Shashikhin</surname>
            <given-names>Vladimir</given-names>
          </name>
        </contrib>
      </contrib-group>
      <aff id="aff1">Peter the Great St. Petersburg Polytechnic University</aff>
      <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-06-30">
        <day>30</day>
        <month>06</month>
        <year>2026</year>
      </pub-date>
      <volume>19</volume>
      <issue>2</issue>
      <fpage>109</fpage>
      <lpage>122</lpage>
      <self-uri xmlns:xlink="http://www.w3.org/1999/xlink" content-type="pdf" xlink:href="https://infocom.spbstu.ru/userfiles/files/articles/2026/2/109-122.pdf"/>
      <abstract xml:lang="en">
        <p>The paper develops an approach to the control of nonlinear dynamic systems within a multicriteria optimization framework in which criterion weights are adjusted during the control process. The method relies on a Lyapunov function that is included both in the performance functional and in trajectory constraints. A numerical algorithm is proposed for dynamic tuning of the criterion weights. The criteria are stability and control energy consumption, while their relative importance changes depending on the current system state and trajectory. Adaptation is performed based on the current value of the Lyapunov function and the system state, which enables automatic prioritization of objectives without operator intervention. A numerical analysis of the system behavior under different weight-adaptation schemes is carried out. For the considered models, the simulation results show that adaptive weight adjustment can provide faster decay of the Lyapunov function and lower control energy consumption compared with fixed scalarization. The method can be applied to control problems for nonlinear and multi-agent systems, including cyber-physical complexes, autonomous agents, and energy nodes.</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>multicriteria optimization</kwd>
        <kwd>Lyapunov function</kwd>
        <kwd>adaptive weights</kwd>
        <kwd>nonlinear systems</kwd>
        <kwd>stability</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <back>
    <ref-list>
      <title>References</title>
      <ref id="ref1">
        <mixed-citation publication-type="journal">Zhadan V.G. Metody optimizatsii. Chast' II. Chislennye algoritmy [Optimization Methods. Part II. Numerical Algorithms]. Moscow: MFTI, 2015.</mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation publication-type="journal">Chernorutskii I.G. Metody optimizatsii v teorii upravleniia [Optimization methods in control theory]. St. Petersburg: Piter, 2004.</mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation publication-type="journal">Prokopenko N.Iu. Metody optimizatsii [Optimization methods]. Nizhny Novgorod: NNGASU, 2018.</mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation publication-type="journal">Kochenderfer M.J., Wheeler T.A. Algorithms for Optimization, 2nd ed. Cambridge, MA; London: MIT Press, 2025.</mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation publication-type="journal">Rostov N.V. Sequential multiobjective parametrical optimization of controllers for nonlinear control system. St. Petersburg State Polytechnical University Journal. Computer Science. Telecommunications and Control Systems, 2010, Vol. 113, No. 6, Pp. 44–50.</mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation publication-type="journal">Rostov N.V. Multiobjective parameter optimization of digital controllers with regard to the influence of nonlinearities and external disturbances. St. Petersburg State Polytechnical University Journal. Computer Science. Telecommunications and Control Systems, 2014, Vol. 193, No. 2, Pp. 91–98.</mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation publication-type="journal">Venkat A.N. Distributed Model Predictive Control: Theory and Applications, PhD dissertation. Madison: University of Wisconsin–Madison, 2006.</mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation publication-type="journal">Tang Y., Wang X. Optimal Output Consensus for Nonlinear Multiagent Systems with Both Static and Dynamic Uncertainties. IEEE Transactions on Automatic Control, 2021, Vol. 66, No. 4. Pp. 1733–1740. DOI: 10.1109/TAC.2020.2996978</mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation publication-type="journal">Fershtadt M.I., Shashikhin V.N. Multi-criteria control of large-scale nonlinear dynamical systems without linearization, based on Lyapunov functions. Computing, Telecommunications and Control, 2025, Vol. 18, No. 4, Pp. 112–122. DOI: 10.18721/JCSTCS.18410</mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation publication-type="journal">Shashikhin V.N., Budnik S.V., Golovina K.O. Control of the spectrum of Lyapunov characteristic exponents in nonlinear large-scale systems. Computing, Telecommunications and Control, 2021, Vol. 14, No. 4, Pp. 37–51. DOI: 10.18721/JCSTCS.14404</mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation publication-type="journal">Zhang C., Fu J. Multi-objective dynamic optimization of path-constrained switched systems. Automa-tica, 2024, Vol. 159, Art. no. 111326. DOI: 10.1016/j.automatica.2023.111326</mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation publication-type="journal">Tao M., Li Q., Yu J. Multi-Objective Dynamic Path Planning with Multi-Agent Deep Reinforcement Learning. Journal of Marine Science and Engineering, 2024, Vol. 13, No. 1, Art. no. 20. DOI: 10.3390/jmse13010020</mixed-citation>
      </ref>
      <ref id="ref13">
        <mixed-citation publication-type="journal">Lin J., He C., Tian Y., Pan L. Variable Reconstruction for Evolutionary Expensive Large-Scale Multiobjective Optimization and Its Application on Aerodynamic Design. IEEE/CAA Journal of Automatica Sinica, 2025, Vol. 12, No. 4, Pp. 719–733. DOI: 10.1109/JAS.2024.124947</mixed-citation>
      </ref>
      <ref id="ref14">
        <mixed-citation publication-type="journal">Zheng Y., Wang Y., Li S. Adaptive control Lyapunov function based model predictive control for continuous nonlinear systems. International Journal of Robust and Nonlinear Control, 2022, Vol. 33, No. 2, Pp. 1254–1266. DOI: 10.1002/rnc.6409</mixed-citation>
      </ref>
      <ref id="ref15">
        <mixed-citation publication-type="journal">Zheng X.-Y., Yan H.-S. Lyapunov-based stochastic model predictive control of stochastic nonlinear systems with input-delay using multi-dimensional Taylor network. Journal of the Franklin Institute, 2025, Vol. 362, No. 9, Art. no. 107694. DOI: 10.1016/j.jfranklin.2025.107694</mixed-citation>
      </ref>
      <ref id="ref16">
        <mixed-citation publication-type="journal">Baheri A. Distributionally robust Lyapunov–Barrier Networks for safe and stable control under uncertainty. Results in Control and Optimization, 2025, Vol. 19, Art. no. 100556. DOI: 10.1016/j.rico.2025.100556</mixed-citation>
      </ref>
      <ref id="ref17">
        <mixed-citation publication-type="journal">Stiti C., Benrabah M., Aouaichia A., Oubelaid A., Bajaj M., Tuka M.B., Kara K. Lyapunov-based neural network model predictive control using metaheuristic optimization approach. Scientific Reports, 2024, Vol. 14, Art. no. 18760. DOI: 10.1038/s41598-024-69365-9</mixed-citation>
      </ref>
      <ref id="ref18">
        <mixed-citation publication-type="journal">Nersesov S.G., Haddad W.M. Control vector Lyapunov functions for large-scale impulsive dynamical systems. Nonlinear Analysis: Hybrid Systems, 2007, Vol. 1, No. 2, Pp. 223–243. DOI: 10.1016/j.nahs.2006.10.006</mixed-citation>
      </ref>
      <ref id="ref19">
        <mixed-citation publication-type="journal">Chen Y.-H. Nonlinear Adaptive Optimal Control Design and Implementation for Trajectory Tracking of Four-Wheeled Mecanum Mobile Robots. Mathematics, 2024, Vol. 12, No. 24, Art. no. 4013. DOI: 10.3390/math12244013</mixed-citation>
      </ref>
      <ref id="ref20">
        <mixed-citation publication-type="journal">Yan Z., Zhang M., Zhou J., Yue L. Distributed Lyapunov-Based Model Predictive Control for AUV Formation Systems with Multiple Constraints. Journal of Marine Science and Engineering, 2024, Vol. 12, No. 3, Art. no. 363. DOI: 10.3390/jmse12030363</mixed-citation>
      </ref>
      <ref id="ref21">
        <mixed-citation publication-type="journal">Peitz S., Dellnitz M. A Survey of Recent Trends in Multiobjective Optimal Control—Surrogate Models, Feedback Control and Objective Reduction. Mathematical and Computational Applications, 2018, Vol. 23, No. 2, Art. no. 30. DOI: 10.3390/mca23020030</mixed-citation>
      </ref>
      <ref id="ref22">
        <mixed-citation publication-type="journal">Wen J., Li L., Wu Q., Li K., Lu J. Multi-Objective Cooperative Adaptive Cruise Control Platooning of Intelligent Connected Commercial Vehicles in Event-Triggered Conditions. Actuators, 2024, Vol. 13, No. 12, Art. no. 522. DOI: 10.3390/act13120522</mixed-citation>
      </ref>
      <ref id="ref23">
        <mixed-citation publication-type="journal">Ionescu C.M., Caruntu C.F., Cajo R., Ghita M., Crevecoeur G., Copot C. Multi-Objective Predictive Control Optimization with Varying Term Objectives: A Wind Farm Case Study. Processes, 2019, Vol. 7, No. 11, Art. no. 778. DOI: 10.3390/pr7110778</mixed-citation>
      </ref>
      <ref id="ref24">
        <mixed-citation publication-type="journal">El Sayed M.A., Farahat A.F., Elsisy M.A., Alsabaan M., Ibrahem M.I., Elwahsh H. Two TOPSIS-Based Approaches for Multi-Choice Rough Bi-Level Multi-Objective Nonlinear Programming Problems. Mathema-tics, 2025, Vol. 13, No. 8, Art. no. 1242. DOI: 10.3390/math13081242</mixed-citation>
      </ref>
      <ref id="ref25">
        <mixed-citation publication-type="journal">Nelyubin A.P., Podinovski V.V. Multicriteria Problems with Importance-Ordered Criteria Groups. Auto-mation and Remote Control, 2022, Vol. 83, Pp. 1108–1122. DOI: 10.1134/S0005117922070074</mixed-citation>
      </ref>
      <ref id="ref26">
        <mixed-citation publication-type="journal">Podinovski V.V., Potapov M.A. Analysis of the Sensitivity of Solutions of Multi-Criteria Problems Based on Parametric Partial Preference Relations. Automation and Remote Control, 2019, Vol. 80, Pp. 1294–1303. DOI: 10.1134/S0005117919070075</mixed-citation>
      </ref>
      <ref id="ref27">
        <mixed-citation publication-type="journal">Balandin D.V., Kogan M.M. Multicriteria Robust Generalized H2 and γ0 Controllers with Applica-tion to Stabilization of a Rotor in Electromagnetic Bearings. Automation and Remote Control, 2018, Vol. 79, Pp. 996–1012. DOI: 10.1134/S0005117918060024</mixed-citation>
      </ref>
      <ref id="ref28">
        <mixed-citation publication-type="journal">Demidenko O.M., Borchik E.M., Yakimov A.I. Multi-criterial optimization of resource distribution in the process of finished products. Problems of Physics, Mathematics and Technics, 2022, Vol. 52, No. 3, Pp. 90–96. DOI: 10.54341/20778708_2022_3_52_90</mixed-citation>
      </ref>
      <ref id="ref29">
        <mixed-citation publication-type="journal">Melnikov A.V., Karavaev A.A., Zheleznyakov A.O. Analysis of the main approaches to modeling management processes for special-purpose organizational and technical systems. Herald of Dagestan State Tech-nical University. Technical Sciences, 2024, Vol. 51, No. 1, Pp. 153–165. DOI: 10.21822/2073-6185-2024-51-1-153-165</mixed-citation>
      </ref>
      <ref id="ref30">
        <mixed-citation publication-type="journal">Belykh M.A. Formalization of a multi-criteria transport task with time constraints. Modeling, Optimi-zation and Information Technology, 2024, Vol. 12, No. 2, Pp. 1–9. DOI: 10.26102/2310-6018/2024.45.2.027</mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>
