Modeling, Simulation, and Dynamic Performance Analysis of an Antenna Azimuth Positioning System

Accurate azimuth positioning is a fundamental requirement for antenna tracking systems because tracking precision directly determines communication reliability and pointing accuracy under dynamic operating conditions. An integrated electromechanical modeling and simulation framework for a closed-loop antenna azimuth positioning system was proposed based on the coupled dynamics of a direct current (DC) servo motor, gear transmission mechanism, and potentiometer-based position feedback. A unified transfer function model was formulated by incorporating the electrical characteristics of the armature circuit and the mechanical dynamics associated with rotational inertia, viscous damping, gear transmission, and power amplification. Three parameterized system configurations were investigated to evaluate the influence of electrical gain, equivalent rotational inertia, and gear transmission ratio on the transient and steady-state characteristics of the positioning system. The simulation results demonstrate that the equivalent rotational inertia exerts the greatest influence on transient response, with the baseline configuration achieving a settling time of approximately 2–3 s, whereas configurations with increased inertia exhibit settling-time increases of approximately 40–60%. Stable closed-loop operation is maintained for all investigated configurations, and the steady-state error is reduced to below 1%, thereby confirming the effectiveness of the feedback control architecture in achieving accurate azimuth positioning. It is further observed that increases in amplifier and motor gains improve response speed but simultaneously increase overshoot and decrease damping margins, thereby revealing a fundamental trade-off between tracking responsiveness and closed-loop robustness. The proposed analytical framework enables systematic evaluation of the influence of electromechanical design parameters on positioning accuracy and dynamic stability while providing quantitative guidance for control-oriented design and parameter selection. The developed modeling methodology establishes a reliable foundation for advanced controller synthesis, including optimal, adaptive, and robust control strategies, and provides a practical basis for real-time implementation and performance optimization of high-precision antenna azimuth positioning systems operating under varying mechanical and electrical conditions.