Auto-Tuning Process of State Feedback Speed Controller Applied for Two-Mass System

Rafal Szczepanski, Marcin Kaminski and Tomasz Tarczewski
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Rafal Szczepanski: Institute of Engineering and Technology, Nicolaus Copernicus University, Grudziadzka 5/7, 87-100 Toruń, Poland
Marcin Kaminski: Department of Electrical Machines, Drives and Measurements, Wroclaw University of Science and Technology, Smoluchowskiego 19, 50-372 Wroclaw, Poland
Tomasz Tarczewski: Institute of Engineering and Technology, Nicolaus Copernicus University, Grudziadzka 5/7, 87-100 Toruń, Poland

Energies, 2020, vol. 13, issue 12, 1-16

Abstract: 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.

Keywords: auto-tuning process; the Artificial Bee Colony algorithm; state feedback controller; two-mass system; optimization; electrical drive system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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