Optimization of Stepper Motor Control in Various Operating Modes

The article investigates the topical issue of increasing the efficiency of stepper motor control, which are key elements in positioning systems within robotic platforms. The possibilities of using three popular controllers are considered and compared: Jetson Nano, ESP32 (as affordable solutions for basic control), and Raspberry Pi 5 (for more complex scenarios due to higher computing power and expanded interfaces). Within the scope of the research, dynamic mathematical models were developed to simulate the loss of control signal at frequencies of 433 MHz, 915 MHz, 2.4 GHz, and 5.8 GHz, taking into account the influence of distance (up to 5000 m) and terrain relief (from -10 to 15 m). The experimental setup included a Nema 17 stepper motor with a TB6600 driver, powered by a 36V battery via a DC/DC converter, with remote control implemented using the CRSF protocol. A separate model was developed to analyze the influence of torque, heat dissipation, and positioning accuracy of the Nema 17 stepper motor at a voltage of 12V and a current of 1.1A. The simulation results demonstrated the dependence of signal loss on distance and terrain relief, as well as the impact of altitude (as a representative of external conditions) on motor temperature and the dependence of positioning accuracy and torque on terrain relief. A comparative analysis of the control platforms was conducted based on the criteria of ease of setup, programming, and debugging, revealing their advantages and limitations for various stepper motor control tasks in robotics. Particular attention was paid to the application of additive technologies (3D printing using a P1P printer and PETg LBL plastic) for rapid prototyping and the fabrication of housing and mounting elements, which significantly optimized the development process. The obtained results contribute to a deeper understanding of the capabilities of various hardware and software tools for the effective control of stepper motors in robotic platforms, considering the influence of external factors and the specifics of remote control. This lays the groundwork for further research in the development of adaptive control systems, energy consumption optimization, and the expansion of the functional capabilities of robotic complexes.