Modeling and Simulation of Single-Phase DC and AC Motor Control Systems Using MATLAB/Simulink Based on First-Order and Second-Order Transfer Functions

Abstract

Electric motor control systems, especially single-phase DC and AC motors, require accurate modeling and simulation approaches to understand the dynamic characteristics and design effective control systems. The main problem addressed in this study is how to model and analyze the dynamic response of the Brushless Silencer BN12HS-28AF-01 DC motor and the single-phase AC motor SIMTACH AC100M-08J30A, both in open-loop and closed-loop configurations, using MATLAB and Simulink software. The main objectives of this study are to develop mathematical models of both motors in the form of first-order and second-order transfer functions, then conduct numerical simulations to verify the stability and performance of the control system in various scenarios. The main contribution of this research lies in the integration of mathematical approaches, identification of actual parameters from datasheets, and the application of MATLAB/Simulink-based simulations to evaluate system performance in the time domain. The method used involves the preparation of transfer functions through Laplace transforms of electrical and mechanical differential models, followed by the implementation of speed control block diagram simulations using step response and system stability testing through time-domain analysis. Simulation results show that in open-loop systems, DC and AC motors tend to have faster rise times, but do not reach a stable steady state and are vulnerable to external disturbances. In contrast, the closed-loop configuration successfully improves transient characteristics and increases system stability. For DC motors, the second-order response shows better damping than the first-order. Single-phase AC motors exhibit more complex dynamics but can still be stabilized with appropriate control parameter settings. In conclusion, MATLAB and Simulink-based simulations are highly effective for validating motor mathematical models and evaluating control system performance. The results can serve as an important basis for developing motor control systems in industry, automation, and engineering education.