doi: 10.17586/2226-1494-2023-23-5-1041-1049


Visual programming environment for multidimensional fuzzy interval-logic regulators

A. F. Antipin, E. V. Antipina


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Antipin A.F., Antipina E.V. Visual programming environment for multidimensional fuzzy interval-logic regulators. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2023, vol. 23, no. 5, pp. 1041–1049 (in Russian). doi: 10.17586/2226-1494-2023-23-5-1041-1049


Abstract
The approach to synthesis and development of multidimensional fuzzy interval-logic regulators in the created visual programming environment that generates the program code of regulators for Simatic S7-300 and S7-400 controllers is considered. Multidimensional interval-logic regulators use the mathematical apparatus of fuzzy regulators with mixed (trapezoidal and rectangular) membership function µ equal to one. The proposed modification of regulators is the author’s development and is intended for use in control systems with a sufficiently large volume of product rules describing the logic of a complex technological object without an adequate mathematical model. The software of the visual development environment takes into account the requirements of the current editions of IEC 61131-3 and 61131-7 standards. The basic variant of the block diagram of a multidimensional interval-logic regulator is presented. Schemes for the interpretation of continuous physical quantities by an equivalent set of terms are given. The proportional deintervalization algorithm is formulated. It is shown that the synthesis and programming of this modification of fuzzy regulators consists in determining the vectors of terms of input and output continuous variables, as well as the mutual relations between them, compiling a system of production rules and selecting the appropriate algorithm of deintervalization. The approach to the development of multidimensional interval-logic regulators by means of special software tools (editors and applications) included in the visual development environment is described. The proposed approach provides a clear and quick creation of controller functional blocks for Simatic S7-300 and S7-400 programmable logic controllers. At the same time, it is possible to analyze and simulate the work of the system of production rules and regulators as a whole, which reduces the time of development and debugging of control systems based on them.

Keywords: fuzzy regulator, visual development environment, editors, production rule system, software

Acknowledgements. This research was funded by the Ministry of Science and Higher Education of the Russian Federation (scientific code FZWU-2023-0002).

References
  1. Filimonov A.B., Filimonov N.B. Sertain problematic aspects of fuzzy pid regulation. Mekhatronika, Avtomatizatsiya, Upravlenie, 2018, vol. 19, no. 12, pp. 762–769. (in Russian). https://doi.org/10.17587/mau/19.762-769
  2. 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, vol. 22,no. 12, pp. 619–624. https://doi.org/10.17587/mau.22.619-624
  3. Kocian J., Koziorek J., Pokorný M. Implementation of fuzzy logic control based on PLC. Proc. of the IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, 2011, pp. 1–8. https://doi.org/10.1109/ETFA.2011.6059049
  4. Burakov M.V., Konovalov A.S., Yakovets O.B. Evolutionary design of fuzzy controllers. Information and Control Systems, 2015, no. 6(79), pp. 28–33. (in Russian). https://doi.org/10.15217/issn1684-8853.2015.6.28
  5. Ignatyev V.V., Solovev V.V. A synthesis method for fuzzy controllers based on clustering. Software & Systems, 2021, vol. 34, no. 4, pp. 597–607. (in Russian). https://doi.org/10.15827/0236-235X.136.597-607
  6. Bogachev I.S., Kolomytsev V.G. Technique for adjusting a fuzzy regulator with a nonlinear P-type characteristic by Matlab. Modern High Technologies, 2020, no. 11-1, pp. 9–14. (in Russian). https://doi.org/10.17513/snt.38330
  7. Buriboev A., Kang H.K., Ko M.-C., Oh R., Abduvaitov A., Jeon H.S. Application of fuzzy logic for problems of evaluating states of a computing system. Applied Sciences, 2019, vol. 9, no. 15, pp. 3021. https://doi.org/10.3390/app9153021
  8. Dumitrescu C., Ciotirnae P., Vizitiu C. Fuzzy logic for intelligent control system using soft computing applications. Sensors, 2021, vol. 21, no. 8, pp. 2617. https://doi.org/10.3390/s21082617
  9. Uskov A.A., Lavrushin V.M. Control systems with fuzzy supervisory PID regulators. Informacionnye tehnologii modelirovanija upravlenija, 2015, vol. 93, no. 3, pp. 279–285. (in Russian)
  10. Vasilev V.I., Iliasov B.G. Intellegent Control Systems. Theory and Practice. Moscow, Radiotehnika Publ., 2009, 388 p. (in Russian)
  11. Piegat A. Fuzzy Modeling and Control. Physica-Verlag HD, 2001, 728 p.
  12. Bobyr M.V., Emelyanov S.G. A nonlinear method of learning neuro-fuzzy models for dynamic control systems. Applied Soft Computing, 2020, vol. 8, pp. 106030. https://doi.org/10.1016/j.asoc.2019.106030
  13. Bobyr M.V., Milostnaya N.A., Kulabuhov S.A. A method of defuzzification based on the approach of areas' ratio. Applied Soft Computing, 2017, vol. 59, pp. 19–32. https://doi.org/10.1016/j.asoc.2017.05.040
  14. Karakuzu C., Karakaya F., Çavuşlu M.A. FPGA implementation of neuro-fuzzy system with improved PSO learning. Neural Networks, 2016, vol. 76, pp. 128–140. https://doi.org/10.1016/j.neunet.2016.02.004
  15. Antipin A.F. The features of the multidimensional logical regulators software implementation with variables as a set of binary logic arguments. Avtomatizacija i sovremennye tehnologii, 2014, no. 2, pp. 30–36. (in Russian)
  16. Antipin A.F. Features of the setup of interlinkages and the creation of the system of condition-action rules in interval-logic controller. Informacionnye sistemy i tehnologii, 2015, no. 1(87), pp. 5–13. (in Russian)
  17. Antipin A.F. Programs evaluation of controllers with programmable logics. Automation and Informatization of the fuel and energy complex, 2018, no. 11, pp. 41–46. (in Russian). https://doi.org/10.30713/0132-2222-2018-11-41-46


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