Advanced Integration of Electromechanical Systems: Enhancing Robot Power Management through Simulation and Control Techniques

Abstract

As robots continue to advance in technology, their applications have expanded across various fields, including manufacturing, services, medical care, search and rescue, and more. However, these robots encounter challenges such as high energy consumption and reliability issues in complex task environments, which hinder their practical application. To address this, the present study focuses on optimizing robot systems through an integrated approach of simulation tools and modern control techniques. Traditional methods for robot energy management have demonstrated limitations when confronted with dynamic and complex environments, often failing to meet the demands for high precision and reliability. This paper first explores the critical role of simulation tools in the design and optimization of robots, highlighting their applications in performance prediction, energy consumption assessment, and control strategy testing. Furthermore, the study elaborates on the latest advancements in adaptive control and model predictive control (MPC) technologies, which enable real-time adjustments to robot operation parameters based on environmental information, thereby achieving more efficient energy management. The integration of these techniques has demonstrated that energy consumption can be reduced by over 20% in various applications, including industrial robots, service robots, and high-technology robots. Additionally, the study discusses future development directions, such as AI-assisted energy management, advanced sensor networks, and the integration of green energy and flexible power supply technologies. In conclusion, this research provides an innovative solution for the efficient operation of robots in complex environments, paving the way for the evolution of robot technology toward more intelligent and sustainable directions.