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Solving the Problem of Discrete Process Control Synthesis Using Optimization on a Sliding Interval

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EN
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EN
The paper brings forward an idea of multi-threaded computation synchronization based on the shared semaphored cache in the multi-core CPUs. It is dedicated to the implementation of multi-core PLC control, embedded solution or parallel computation of models described using hardware description languages. The shared semaphored cache is implemented as guarded memory cells within a dedicated section of the cache memory that is shared by multiple cores. This enables the cores to speed up the data exchange and seamlessly synchronize the computation. The idea has been verified by creating a multi-core system model using Verilog HDL. The simulation of task synchronization methods allows for proving the benefits of shared semaphored memory cells over standard synchronization methods. The proposed idea enhances the computation in the algorithms that consist of relatively short tasks that can be processed in parallel and requires fast synchronization mechanisms to avoid data race conditions.
Twórcy
  • Academy of Logistics and Transport, Almaty Technological University, Almaty, Kazakhstan
  • Lublin University of Technology, Lublin, Poland
  • Turan University and Satbayev University, Almaty, Kazakhstan
  • Almaty Technological University, Almaty, Kazakhstan
  • Almaty Technological University, Almaty, Kazakhstan
Bibliografia
  • [1] V.P. Safronova, and M.V. Yakovleva, “Microprocessor Controllers of Automatic Systems and Automatic Control Systems,” in proc. 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), pp. 319-321, 2019. https://doi.org/10.1109/EIConRus.2019.8656677
  • [2] E. P. Ivanova, “Differential-difference equations with incommensurable shifts of arguments,” in Proceedings of the Voronezh Spring Mathematical School "Modern methods in the theory of boundary value problems. Pontryagin readings-XXX", Voronezh, May 3-9, vol. 191, no. 0, pp. 92-100, 2021. https://doi.org/10.36535/0233-6723-2021-191-92-100
  • [3] V. N. Panovskiy, A. V. Panteleev, “Meta-heuristic interval methods of search of optimal in average control of nonlinear determinate systems with incomplete information about its parameters,” Journal of Computer and Systems Sciences International, vol. 56, no. 1, pp. 52-63, 2017. https://doi.org/10.1134/S1064230717010117
  • [4] A. S. Antipov, D. V. Krasnov, A. V. Utkin, “Decomposition synthesis of the control system of electromechanical objects in conditions of incomplete information,” Mechanics of Solids, vol. 54, no. 5, pp. 669-682, 2019. https://doi.org/10.3103/S0025654419050042
  • [5] F. A. Aliev et al., “Larin Parameterization to Solve the Problem of Analytical Construction of the Optimal Regulator of Oscillatory Systems with Liquid Dampers,” Journal of Applied and Computational Mechanics, vol. 6, special issue, pp. 1426-1430, 2020. https://doi.org/10.22055/JACM.2020.34950.2548
  • [6] R. F. Stengel, “Flight dynamics,” Princeton University press, 2022.
  • [7] A. T. Saidmamatov, “Theory of Optimal Design of Construction,” Eurasian Journal of Engineering and Technology, no. 11, pp.43-48, 2022. https://www.geniusjournals.org/index.php/ejet/article/view/2325
  • [8] X. H. Chang, R. R. Liu, and J. H. Park, “A Further Study on Output Feedback H∞ Control for Discrete-Time Systems,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 67, no. 2, pp. 305-309, 2019. https://doi.org/10.1109/TCSII.2019.2904320
  • [9] E. Isufi, A. Loukas, N. Perraudin, and G. Leus, “Forecasting Time Series With VARMA Recursions on Graphs,” IEEE Transactions on Signal Processing, vol. 67, no. 18, pp. 4870-4885, 2019. https://doi.org/10.1109/TSP.2019.2929930
  • [10] N. V. Balashevich, R. Gabasov, and F. M. Kirillova, “Numerical methods for open-loop and closed-loop optimization of linear control systems,” Computational mathematics and mathematical physics, vol. 40, no. 6, pp. 799-819, 2000. https://www.mathnet.ru/eng/zvmmf1260
  • [11] N. A. Dyakonov, and O. S. Logunova, “Process control systems based on predictive analytics: design,” Electrotechnical systems and complexes, no. 1, vol. 50, pp. 58-64, 2021.
  • [12] O. Vasilevskyi, P. Kulakov, D. Kompanets, O. M. Lysenko, V. Prysyazhnyuk, W. Wójcik, and D. Baitussupov, “A new approach to assessing the dynamic uncertainty of measuring devices,” in Proc. SPIE, vol. 10808, pp. 728-735, 2018. https://doi.org/10.1117/12.2501578
  • [13] I. V. Gogol, O. A. Remizova, V. V. Syrokvashin, and A. L. Fokin, “Adaptive-robust control of technological processes with delay on control,” in: Kravets, A., Bolshakov, A., Shcherbakov, M. (eds) Cyber-Physical Systems: Industry 4.0 Challenges. Studies in Systems, Decision and Control, vol 260, Springer, Cham, 2020. https://doi.org/10.1007/978-3-030-32648-7_11
  • [14] A. P. Pandey, and M. C. de Oliveira, “Discrete-time H∞ control of linear parameter-varying systems,” International Journal of Control, vol. 12, no. 92, pp. 2750-2760, 2019. https://doi.org/10.1080/00207179.2018.1459855
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-804e34c2-0e03-436e-858a-76d27a80ef8d
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