<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">mireabulletin</journal-id><journal-title-group><journal-title xml:lang="ru">Russian Technological Journal</journal-title><trans-title-group xml:lang="en"><trans-title>Russian Technological Journal</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2782-3210</issn><issn pub-type="epub">2500-316X</issn><publisher><publisher-name>RTU MIREA</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.32362/2500-316X-2025-13-3-54-62</article-id><article-id custom-type="edn" pub-id-type="custom">SHAEZM</article-id><article-id custom-type="elpub" pub-id-type="custom">mireabulletin-1177</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>РОБОТИЗИРОВАННЫЕ КОМПЛЕКСЫ И СИСТЕМЫ. ТЕХНОЛОГИИ ДИСТАНЦИОННОГО ЗОНДИРОВАНИЯ НЕРАЗРУШАЮЩЕГО КОНТРОЛЯ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>MULTIPLE ROBOTS (ROBOTIC CENTERS) AND SYSTEMS. REMOTE SENSING AND NON-DESTRUCTIVE TESTING</subject></subj-group></article-categories><title-group><article-title>Анализ и синтез интеллектуальных систем автоматического управления с нечетким регулятором I рода</article-title><trans-title-group xml:lang="en"><trans-title>Analysis and synthesis of intelligent automatic control systems with type-1 fuzzy regulator</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0003-6671-5674</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Быковцев</surname><given-names>Ю. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Bykovtsev</surname><given-names>Yu. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Быковцев Юрий Алексеевич, к.т.н., доцент, кафедра проблем управления 119454, Россия, Москва, пр-т Вернадского, д 78 Scopus Author ID 57302607300ResearcherID KRQ-5339-2024</p></bio><bio xml:lang="en"><p>Yuri A. Bykovtsev, Cand. Sci. (Eng.), Assistant Professor, Department of Management Problems 78, Vernadskogo pr., Moscow, 119454 RussiaScopus Author ID 57302607300 ResearcherID KRQ-5339-2024</p></bio><email xlink:type="simple">bykovcev@mirea.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-6708-9124</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Лохин</surname><given-names>В. М.</given-names></name><name name-style="western" xml:lang="en"><surname>Lokhin</surname><given-names>V. M.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Лохин Валерий Михайлович, д.т.н., профессор, кафедра проблем управления. Лауреат государственной премии РФ в области науки и техники. Лауреат премии Правительства РФ в области образования. Член научного Совета РАН по робототехнике и мехатронике. Заслуженный деятель науки РФ. 119454, Россия, Москва, пр-т Вернадского, д. 78  Scopus Author ID 6602931640</p></bio><bio xml:lang="en"><p>Valery M. Lokhin, Dr. Sci. (Eng.), Professor, Department of Management Problems. Laureate of the State Prize of the Russian Federation in Science and Technology. Laureate of the State Prize of the Russian Federationin Education. Member of the Scientific Council on Robotics and Mechatronics of the Russian Academy of Sciences. Honored Worker of Science of the Russian Federation. 78, Vernadskogopr., Moscow, 119454 Russia Scopus Author ID 6602931640</p></bio><email xlink:type="simple">kpu-mirea@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Институт искусственного интеллекта, ФГБОУ ВО «МИРЭА – Российский технологический университет»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Institute of Artificial Intelligence, MIREA – Russian Technological University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>05</day><month>06</month><year>2025</year></pub-date><volume>13</volume><issue>3</issue><fpage>54</fpage><lpage>62</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Быковцев Ю.А., Лохин В.М., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Быковцев Ю.А., Лохин В.М.</copyright-holder><copyright-holder xml:lang="en">Bykovtsev Y.A., Lokhin V.M.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.rtj-mirea.ru/jour/article/view/1177">https://www.rtj-mirea.ru/jour/article/view/1177</self-uri><abstract><p>Цели. Активное развитие интеллектуальных систем автоматического управления, связанное с повышением требований к качеству и точности систем управления современных технических систем, требует разработки новых подходов к их анализу и синтезу. Одним из перспективных классов интеллектуальных управляющих устройств выступают регуляторы, построенные на базе технологии нечеткого логического вывода. Целью настоящей работы является разработка методики комплексного синтеза параметров нечеткого регулятора I рода на основе кругового критерия Якубовича.Методы. В основу предлагаемой методики положено рассмотрение нечеткого регулятора с позиции соответствующего нелинейного преобразования, что позволяет использовать методы теории нелинейных систем автоматического управления. В качестве показателей качества в работе используются аналоги понятий «степень устойчивости» и «степень колебательности». Синтез параметров нелинейного преобразования сводится к определению достаточных областей абсолютной устойчивости системы со смещенной и расширенной амплитудно-фазовыми частотными характеристиками, полученных с помощью кругового критерия устойчивости Якубовича.Результаты. В соответствии с теорией нечетких множеств и алгоритмом нечеткого логического вывода Такаги – Сугено показана возможность взаимно-однозначного соответствия нелинейного преобразования и параметров базы знаний нечеткого регулятора при соответствующей организации последней. В работе предложена процедура синтеза параметров нечеткого регулятора I рода, нацеленная на обеспечение комплексных требований к качеству системы управления по «степени устойчивости», «степени колебательности» и точности в установившемся режиме. Предложенная методика также гарантирует абсолютную устойчивость не только положения равновесия, но и процессов, а ее эффективность подтверждена результатами модельных экспериментов.Выводы. В работе предложена удобная инженерная методика настройки параметров интеллектуального регулятора, построенная по технологии нечеткого логического вывода на основе методов теории автоматического управления. Показано удобство применения таких косвенных показателей качества, как «степень устойчивости», «степень колебательности» и точность в установившемся режиме. </p></abstract><trans-abstract xml:lang="en"><p>Objectives. The active development of intelligent automatic control systems, which is associated with increasing requirements to the quality and accuracy of control systems of modern technical systems, requires the development of new approaches to their analysis and synthesis. A promising class of intelligent control devices is based on regulators that use fuzzy-logic inference technology. The purpose of this work is to develop a method for the complex synthesis of type-1 fuzzy regulator parameters on the basis of the Yakubovich circle criterion.Methods. The proposed methodology is based on a consideration of fuzzy regulators in terms of the corresponding nonlinear transformation that support the use of methods derived from the theory of nonlinear automatic control systems. Analogs of the degrees of stability and oscillation are used as quality indicators. The synthesis of the parameters of the nonlinear transformation can be reduced to determining sufficient regions of absolute stability of the system with the shifted and extended Nyquist plot obtained using the Yakubovich circle stability criterion.Results. In accordance with the theory of fuzzy sets and algorithms of fuzzy logical inference described by Takagi–Sugeno, the possibility of one-to-one correspondence of the nonlinear transformation and the parameters of an appropriately arranged knowledge base of the fuzzy controller is shown. A procedure proposed for synthesizing the parameters of the type-1 fuzzy regulator is aimed at ensuring complex requirements for the quality of the control system according to the degree of stability, the degree of oscillation, and steady-state mode accuracy. The effectiveness of the proposed technique, which guarantees the absolute stability not only of the equilibrium position but also of the processes, is confirmed by the results of model experiments.Conclusions. The paper proposes a convenient engineering technique for determining the parameters of an intelligent controller constructed using fuzzy logic inference technology based on methods informed by automatic control theory. The convenience of using such indirect quality indicators as the degree of stability, the degree of oscillation, and accuracy in steady-state mode, is demonstrated. These indicators are explicable for developers of applied control systems.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>интеллектуальная система управления</kwd><kwd>нечеткий логический вывод</kwd><kwd>нечеткий регулятор</kwd><kwd>модель Такаги – Сугено</kwd><kwd>абсолютная устойчивость процессов</kwd></kwd-group><kwd-group xml:lang="en"><kwd>intelligent control system</kwd><kwd>fuzzy logic inference</kwd><kwd>fuzzy controller</kwd><kwd>Takagi–Sugeno model</kwd><kwd>absolute stability of processes</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Макаров И.М., Лохин В.М. Интеллектуальные системы автоматического управления. М.: Физматлит; 2001. 576 с. ISBN 978-5-9221-0162-2</mixed-citation><mixed-citation xml:lang="en">Makarov I.M., Lokhin V.M. Intellektual’nye sistemy avtomaticheskogo upravleniya (Intelligent Automatic Control Systems). Moscow: Fizmatlit; 2001. 576 p. (in Russ.). ISBN 978-5-9221-0162-2</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Поспелов Д.А. (ред.). Нечеткие множества в моделях управления и искусственного интеллекта. М.: Наука; 1986. 312 с.</mixed-citation><mixed-citation xml:lang="en">Pospelov D.A. (Ed.). Nechetkie mnozhestva v modelyakh upravleniya i iskusstvennogo intellekta (Fuzzy Sets in Control Models and Artificial Intelligence). Moscow: Nauka; 1986. 312 p. (in Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Макаров И.М., Лохин В.М., Манько С.В., Романов М.П. Искусственный интеллект и интеллектуальные системы управления. М.: Наука; 2006. 333 с.</mixed-citation><mixed-citation xml:lang="en">Makarov I.M., Lokhin V.M., Manko S.V., Romanov M.P. Iskusstvennyi intellekt i intellektual’nye sistemy upravleniya(Artificial Intelligence and Intelligent Control Systems). Moscow: Nauka; 2006. 333 p. (in Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Makarov I.M., Lokhin V.M. Artificial Intelligence and Complex Objects Control. Lewiston: Edwin Mellen Press; 2000. 404 p.</mixed-citation><mixed-citation xml:lang="en">Makarov I.M., Lokhin V.M. Artificial Intelligence and Complex Objects Control. Lewiston: Edwin Mellen Press; 2000. 404 p.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Piegat A. Fuzzy Modeling and Control. Berlin: Physica Heidelberg; 2001. 728 p.</mixed-citation><mixed-citation xml:lang="en">Piegat A. Fuzzy Modeling and Control. Berlin: Physica Heidelberg; 2001. 728 p.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Макаpов И.М., Лохин В.М., Манько С.В., Романов М.П., Ситников М.С. Устойчивость интеллектуальных систем автоматического управления. Информационные технологии. 2013;2:1–32.</mixed-citation><mixed-citation xml:lang="en">Makarov I.M., Lokhin V.M., Manko S.V., Romanov M.P., Sitnikov M.S. Stability of intellectual automatic control systems. Informatsionnye tekhnologii = Information Technologies. 2013;2:1–32 (in Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Рутковская Д., Пилиньский М., Рутковский Л. Нейронные сети, генетические алгоритмы и нечеткие системы: пер. с пол. М.: Горячая линия–Телеком; 2006. 452 с.</mixed-citation><mixed-citation xml:lang="en">Rutkowska D., Pilinski M., Rutkowski L. Neironnye seti, geneticheskie algoritmy i nechetkie sistemy (Neural Networks, Genetic Algorithms and Fuzzy Systems): transl. from Pol. Moscow: Goryachaya liniya–Telekom; 2006. 452 p. (in Russ.). [Rutkowska D., Piliński M., Rutkowski L. Sieci Neuronowe, Algorytmy Genetyczne i Systemy Rozmyte. Warszawa; Łodż: Wydawnictwo Naukowe PWN. 2004.]</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Hashemi S.M., Botez R. Lyapunov-based Robust Adaptive Configuration of the UAS-S4 Flight Dynamics Fuzzy Controller. The Aeronautical Journal. 2022;126(1301):1187–1209. https://doi.org/10.1017/aer.2022.2</mixed-citation><mixed-citation xml:lang="en">Hashemi S.M., Botez R. Lyapunov-based Robust Adaptive Configuration of the UAS-S4 Flight Dynamics Fuzzy Controller. The Aeronautical Journal. 2022;126(1301):1187–1209. https://doi.org/10.1017/aer.2022.2</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Gandhi R., Adhyaru D. Takagi-Sugeno fuzzy regulator design for nonlinear and unstable systems using negative absolute eigenvalue approach. IEEE/CAA Journal of Automatica Sinica. 2020,7(2):482–493. https://doi.org/10.1109/JAS.2019.1911444</mixed-citation><mixed-citation xml:lang="en">Gandhi R., Adhyaru D. Takagi-Sugeno fuzzy regulator design for nonlinear and unstable systems using negative absolute eigenvalue approach. IEEE/CAA Journal of Automatica Sinica. 2020;7(2):482–493. https://doi.org/10.1109/JAS.2019.1911444</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Lan L., Tiem N., Co Nhu V. Absolute Stability for a Class of Takagi-Sugeno Fuzzy Control Systems. In: 3rd International Conference on Robotics, Control and Automation Engineering (RCAE). 2020. P. 47–51. https://doi.org/10.1109/RCAE51546.2020.9294352</mixed-citation><mixed-citation xml:lang="en">Lan L., Tiem N., Co Nhu V. Absolute Stability for a Class of Takagi-Sugeno Fuzzy Control Systems. In: 3rd International Conference on Robotics, Control and Automation Engineering (RCAE). 2020. P. 47–51. https://doi.org/10.1109/RCAE51546.2020.9294352</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Sakly A., Zahra B., Benrejeb M. Stability Study of Mamdani’s Fuzzy Controllers Applied to Linear Plants. Studies in Informatics and Control. 2008;17(4):441–452.</mixed-citation><mixed-citation xml:lang="en">Sakly A., Zahra B., Benrejeb M. Stability Study of Mamdani’s Fuzzy Controllers Applied to Linear Plants. Studies in Informatics and Control. 2008;17(4):441–452.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Siddikov I., Porubay O., Rakhimov T. Synthesis of the neuro-fuzzy regulator with genetic algorithm. Int. J. Electric. Comput. Eng. (IJECE). 2024;14(1):184–191. http://doi.org/10.11591/ijece.v14i1.pp184-191</mixed-citation><mixed-citation xml:lang="en">Siddikov I., Porubay O., Rakhimov T. Synthesis of the neuro-fuzzy regulator with genetic algorithm. Int. J. Electric. Comput. Eng. (IJECE). 2024;14(1):184–191. http://doi.org/10.11591/ijece.v14i1.pp184-191</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Hamza M., Yap I., Choudhury I. Genetic Algorithm and Particle Swarm Optimization Based Cascade Interval Type 2 Fuzzy PD Controller for Rotary Inverted Pendulum System. Math. Probl. Eng. 2015;2015(6). https://doi.org/10.1155/2015/695965</mixed-citation><mixed-citation xml:lang="en">Hamza M., Yap I., Choudhury I. Genetic Algorithm and Particle Swarm Optimization Based Cascade Interval Type 2 Fuzzy PD Controller for Rotary Inverted Pendulum System. Math. Probl. Eng. 2015;2015(6). https://doi.org/10.1155/2015/695965</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Mahmoodabadi M., Babak N. Robust fuzzy linear quadratic regulator control optimized by multi-objective high exploration particle swarm optimization for a 4 degree-of-freedom quadrotor. Aerosp. Sci. Technol. 2019;97:105598. https://doi.org/10.1016/j.ast.2019.105598</mixed-citation><mixed-citation xml:lang="en">Mahmoodabadi M., Babak N. Robust fuzzy linear quadratic regulator control optimized by multi-objective high exploration particle swarm optimization for a 4 degree-of-freedom quadrotor. Aerosp. Sci. Technol. 2019;97:105598. https://doi.org/10.1016/j.ast.2019.105598</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Sakalli A., Beke A., Kumbasar T. Gradient Descent and Extended Kalman Filter based self-tuning Interval Type-2 Fuzzy PID controllers. In: 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). 2016. P. 1592–1598. https://doi.org/10.1109/FUZZ-IEEE.2016.7737880</mixed-citation><mixed-citation xml:lang="en">Sakalli A., Beke A., Kumbasar T. Gradient Descent and Extended Kalman Filter based self-tuning Interval Type-2 Fuzzy PID controllers. In: 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). 2016. P. 1592–1598. https://doi.org/10.1109/FUZZ-IEEE.2016.7737880</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Islam S.U., Zeb K., Kim S. Design of Robust Fuzzy Logic Controller Based on Gradient Descent Algorithm with Parallel-Resonance Type Fault Current Limiter for Grid-Tied PV System. Sustainability. 2022;14(19):12251. https://doi.org/10.3390/su141912251</mixed-citation><mixed-citation xml:lang="en">Islam S.U., Zeb K., Kim S. Design of Robust Fuzzy Logic Controller Based on Gradient Descent Algorithm with ParallelResonance Type Fault Current Limiter for Grid-Tied PV System. Sustainability. 2022;14(19):12251. https://doi.org/10.3390/su141912251</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Быковцев Ю.А. Синтез нечеткого регулятора на основе оценки степени устойчивости системы управления. Мехатроника, автоматизация, управление. 2022;23(6):295–301. https://doi.org/10.17587/mau.23.295-301</mixed-citation><mixed-citation xml:lang="en">Bykovtsev Y.A. Synthesis of a Fuzzy Controller According to the Degree of Stability of the Control System. Mekhatronika, Avtomatizatsiya, Upravlenie. 2022;23(6):295–301 (in Russ.). https://doi.org/10.17587/mau.23.295-301</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Bykovtsev Y.A., Lokhin V.M. Estimation of the accuracy of a control system with a fuzzy PID controller based on the approximation of the static characteristic of the controller. Mekhatronika, Avtomatizatsiya, Upravlenie. 2021;22(12):619–624. https://doi.org/10.17587/mau.22.619-624</mixed-citation><mixed-citation xml:lang="en">Bykovtsev Y.A., Lokhin V.M. Estimation of the accuracy of a control system with a fuzzy PID controller based on the approximation of the static characteristic of the controller. Mekhatronika, Avtomatizatsiya, Upravlenie. 2021;22(12):619–624. https://doi.org/10.17587/mau.22.619-624</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
