Drive Control for Multi-Motor Systems: Strategies and Performance Optimization

Abstract

Multi-motor systems (MMS) are widely used in industrial robotics, electric vehicles, conveyor networks, and automation systems. Coordinated control of multiple motors is critical to ensure synchronization, load sharing, and energy efficiency. This paper investigates drive control strategies for multi-motor systems, including master-slave control, decentralized control, and model predictive control (MPC). Simulation and experimental results demonstrate synchronized torque and speed control, reduced energy consumption, and improved dynamic response. Findings highlight that optimized multi-motor drive control enhances system reliability and performance in industrial applications.

Multi-motor systems (MMS) are widely used in industrial robotics, electric vehicles, conveyor networks, and automation systems. Coordinated control of multiple motors is critical to ensure synchronization, load sharing, and energy efficiency. This paper investigates drive control strategies for multi-motor systems, including master-slave control, decentralized control, and model predictive control (MPC). Simulation and experimental results demonstrate synchronized torque and speed control, reduced energy consumption, and improved dynamic response. Findings highlight that optimized multi-motor drive control enhances system reliability and performance in industrial applications.

KEYWORDS: Multi-motor systems, Drive control, Synchronization, Master-slave control, Model predictive control, Industrial automation. Multi-motor systems, Drive control, Synchronization, Master-slave control, Model predictive control, Industrial automation.