Artificial bee colony based auto-tuning of PMSM state feedback speed controller

Author(s):  
Tomasz Tarczewski ◽  
Lech M. Grzesiak
2019 ◽  
Vol 28 ◽  
pp. 01031
Author(s):  
Rafal Szczepanski ◽  
Tomasz Tarczewski ◽  
Lech M. Grzesiak

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 can be used to reduce computation time by using parallel computing. 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.


Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3067
Author(s):  
Rafal Szczepanski ◽  
Marcin Kaminski ◽  
Tomasz Tarczewski

The state feedback controller is increasingly applied in electrical drive systems due to robustness and good disturbance compensation, however its main drawback is related to complex and time consuming tuning process. It is particularly troublesome for designer, if the plant is compound, nonlinear elements are taken into account, measurement noise is considered, etc. In this paper the application of nature-inspired optimization algorithm to automatic tuning of state feedback speed controller (SFC) for two-mass system (TMS) is proposed. In order to obtain optimal coefficients of SFC, the Artificial Bee Colony algorithm (ABC) is used. The objective function is described and discussed in details. Comparison with analytical tuning method of SFC is also included. Additionally, the stability analysis for the control system, optimized using the ABC algorithm, is presented. Synthesis procedure of the controller is utilized in Matlab/Simulink from MathWorks. Next, obtained coefficients of the controller are examined on the laboratory stand, also with variable moment of inertia values, to indicate robustness of the controller with optimal coefficients.


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