Efficiency analysis of parallel computing applied to auto-tuning of state feedback speed controller for PMSM drive

• Autorzy: Szczepański Rafał , Tarczewski Tomasz , Grzesiak Lech M.

Identyfikatory

DOI

10.21008/j.1897-0737.2019.100.0013

• Konferencja: Computer Applications in Electrical Engineering (15-16.04.2019 ; Poznań, Polska)
• Języki publikacji: EN

Abstrakty

EN

Nowadays the simulation is inseparable part of researcher's work. Its computation time may significantly exceed the experiment time. On the other hand, multi-core processors are common in personal computers. These processors can be used to reduce computation time by using parallel computing on multiple cores. The most popular software applied to simulate behavior of the plant is MATLAB/Simulink. A single simulation of Simulink model cannot be computed by multiple cores, but there are many engineering problems, that require a multiple simulation of the same model with different parameters. In these problems, the parallel computing can be employed to decrease the overall simulation time. In this paper the parallel computing is used to speed-up the auto-tuning process of state feedback speed controller for PMSM drive. In order to obtain the optimal coefficients of the controller, an Artificial Bee Colony optimization algorithm is employed.

Słowa kluczowe

EN

parallel computing; Artificial Bee Colony; PMSM; state feedback; controller; MATLAB/Simulink

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Poznan University of Technology Academic Journals. Electrical Engineering
• Rocznik: 2019
• Tom: No. 100
• Strony: 145--156
• Opis fizyczny: Bibliogr. 12 poz., rys., tab.

Twórcy

autor

Szczepański Rafał

• Nicolaus Copernicus University

autor

Tarczewski Tomasz

• Nicolaus Copernicus University

autor

Grzesiak Lech M.

• Warsaw University of Technology

Bibliografia

• [1] Open Multi-processing homepage (www.openmp.org).
• [2] Message Passing Interface homepage (www.mpi-forum.org).
• [3] MathWorks, Parallel Computing Toolbox homepage (www.mathworks.com/products/parallel-computing.html).
• [4] Liu X., Chen H., Zhao X., Belahcen A., Research on the Performances and Parameters of Interior PMSM Used for Electric Vehicles, IEEE Transactions on Industrial Electronics, vol. 63, no. 6, pp. 3533–3545, 2016.
• [5] Faa-Jeng Lin, Hsin-Jang Shieh, Po-Huang Shieh, Po-Hung Shen, An adaptive recurrent-neural-network motion controller for X-Y table in CNC Machine, in IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 36, no. 2, pp. 286–299, 2006.
• [6] Zhong L., Rahman M.F., Hu W.Y., Lim K.W., Analysis of direct torque control in permanent magnet synchronous motor drives, in IEEE Transactions on Power Electronics, vol. 12, no. 3, pp. 528–536, 1997.
• [7] Jarzebowicz L., Error analysis of calculating average dq current components using regular sampling and Park transformation in FOC drives, in Proc. IEEE Intern. Conf. EPE 2014, pp. 901–905, 2014.
• [8] Franklin G.F., Powell J.D., Emami-Naeini A., Powell J.D., (1994), Feedback control of dynamic systems, vol. 3, Reading, MA: Addison-Wesley.
• [9] Kamiński M., Application of the BAT algorithm in optimization of adaptive state space controller used for two-mass system, Przegląd Elektrotechniczny, vol. 93, no.1, pp. 300–304, 2017, (in Polish).
• [10] Karaboga D., Basturk B., Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems. In: Melin P., Castillo O., Aguilar L.T., Kacprzyk J., Pedrycz W. (eds) Foundations of Fuzzy Logic and Soft Computing, IFSA 2007, Lecture Notes in Computer Science, vol. 4529. Springer, Berlin, Heidelberg.
• [11] Tarczewski T., Grzesiak L.M., An Application of Novel Nature-Inspired Optimization Algorithms to Auto-Tuning State Feedback Speed Controller for PMSM, IEEE Transactions on Industry Applications, vol. 54, no. 3, pp. 2913–2925, 2018.
• [12] Deb K., An efficient constraint handling method for genetic algorithms. Comput. Meth. Appl. Mech. Eng., vol. 186, pp. 311–338, 2000.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).