Abstract
The method of simulation structural-complex continuous-discrete control systems is discussed. For simulation and calculation of dynamic processes in continuous-discrete systems topological interpolation method is proposed, based on application of hybrid methods of space of state variables and interpolation of signals. The essence of the method is that the dynamics of the investigated system, considered at the final interval, is broken down into subintervals, on each of which the processes are described by linear ordinary system differential equations. The computational efficiency of the proposed method was evaluated by comparison with standard methods such as the Runge-Kutta-Merson method. The use of this method to calculate the dynamic processes described by the non-linear or piecemeal differential equations with the right breaking part allows to reduce the number of calculations by 2^n-1 times compared to the known methods and to eliminate operations related to decomposition of the fundamental matrix in the Taylor power series.
First Page
40
Last Page
51
References
- Umurzakova D.M. (2022). System of automatic control of the level of steam power generators on the basis of the regulation circuit with smoothing of the signal. IIUM Engineering Journal, 22(1), 287-297. https://doi.org/10.31436/iiumej.v22i1.1415.
- Umurzakova, D.M. (2020). Mathematical Modeling of Transient Processes of a Three-pulse System of Automatic Control of Water Supply to the Steam Generator When the Load Changes. 14th International IEEE Scientific and Technical Conference Dynamics of Systems, Mechanisms and Machines, Dynamics 2020 – Proceedings. https://doi.org/10.1109/Dynamics50954.2020.9306117.
- Siddikov, I.X., Umurzakova, D.M. (2021). Simulation of a Two-level Control System for Nonlinear Dynamic Objects with a Neurofuzzy Adaptive Regulator. International conference on information science and communications technologies applications, trends and opportunities (ICISCT 2021). Tashkent. https://doi.org/10.1109/ICISCT52966.2021.9670075.
- Zhu, X., Zhang, H., Cao, D., Fang, Z. (2014). Robust control of integrated motor-transmission powertrain system over controller area network for automotive applications. Mechanical Systems and Signal Processing. 58, 15-28.
- Zulfatman and M.F.Rahmat (2009). Application of self-tuning Fuzzy PID controller on industrial hydraulic actuator using system identification approach. International Journal on Smart Sensing and Intelligent Systems, 2(2), 246-261.
- Das, S., Pan, I., Halder, K., Das, S., Gupta, A. (2013). LQR based improved discrete PID controller design via optimum selection of weighting matrices using fractional order integral performance index. Applied Mathematical Modelling: Simulation and Computation for Engineering and Environmental Systems, 37(6), 4253-4268.
- Gasbaoui, B., Nasri, A. (2012). A novel multi-drive electric vehicle system control based on multi-input multi-output PID controller. Serbian Journal of Electrical Engineering, 9(2), 279-291.
- Has, Z., Muslim, A.H., Mardiyah, N.A. (2017). Adaptive-fuzzy-PID controller based disturbance observer for DC motor speed control. 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), 1-6.
- Hu, S., Liang, Z., Zhang, W., He, X. (2018). Research on the integration of hybrid energy storage system and dual three-phase PMSM Drive in EV. IEEE Transactions on Industrial Electronics, 65(8), 6602–6611.
- Iplikci, S. (2010). A comparative study on a novel model-based PID tuning and control mechanism for nonlinear systems. International Journal of Robust and Nonlinear Control, 20(13), 1483-1501.
- Jaiswal, M., Phadnis, M., Ex, H.O.D. (2013). Speed control of DC motor using genetic algorithm based PID controller. International Journal of Advanced Research in Computer Science and Software Engineering, 3(7), 2277–2288.
- Kalangadan, A., Priya, N., Kumar, T.K.S. (2015). PI, PID controller design for interval systems using frequency response model matching technique. in Proceedings of the International Conference on Control, Communication and Computing India, ICCC 2015. 119-124.
- Kumar, S.M.G., Deepak, J., Anoop, R.K. (2010). PSO based tuning of a PID controller for a High performance drilling machine. International Journal of Computer Applications, 1(19), 12-18.
- Lu, C., Hsu, C., Juang, C. (2013). Coordinated control of flexible AC transmission system devices using an evolutionary fuzzy lead-lag controller with advanced continuous ant colony optimization. IEEE Transactions on Power Systems, 28(1), 385-392.
- Malwatkar, G.M., Khandekar, A.A., Nikam, S.D. (2011). PID controllers for higher order systems based on maximum sensitivity function. 3rd International Conference on Electronics Computer Technology.
- Pelusi, D. (2012). PID and intelligent controllers for optimal timing performances of industrial actuators. International Journal of Simulation: Systems, Science and Technology, 13(2), 65-71.
- Pelusi, D., Mascella, R. (2013). Optimal control algorithms for second order systems. Journal of Computer Science, 9(2), 183-197.
Recommended Citation
Siddikov, Isamiddin Xakimovich and Umurzakova, Dilnoza Maxamadjanovna
(2023)
"TOPOLOGICAL INTERPOLATION METHOD FOR MODELING DYNAMIC SYSTEMS,"
Chemical Technology, Control and Management: Vol. 2023:
Iss.
3, Article 6.
DOI: https://doi.org/10.59048/2181-1105.1465
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