Salzburg University of Applied Sciences and ABB’s Machine Automation division (B&R) have jointly filed a patent application for a new artificial intelligence-based approach aimed at reducing energy consumption in industrial motion control systems used across manufacturing environments.
A research partnership between Salzburg University of Applied Sciences and ABB’s Machine Automation division, B&R, has resulted in a patent application focused on improving the energy efficiency of industrial drive systems through artificial intelligence.
The development emerged from work conducted at the Josef Ressel Center for Intelligent and Secure Industrial Automation (JRZ ISIA), where researchers and industry experts have been exploring ways to optimize the performance of motion-controlled systems used in robots, machine tools and automated production lines.
The patent centers on a method for energy-optimized motion control in applications that require highly precise movements, including positioning, acceleration, deceleration and repetitive production cycles. According to the project partners, conventional control systems rely heavily on mathematical models that may not fully account for energy losses occurring in real-world operating conditions.
To address this challenge, the research team is applying reinforcement learning, a branch of artificial intelligence that enables systems to improve performance through interaction and experience. In the proposed approach, a learning agent operates directly on physical equipment, identifying how different motion patterns influence energy consumption and adjusting control strategies without requiring a complete system model.
Researchers say a key aspect of the innovation is a mathematical framework designed to accelerate the learning process while reducing the amount of data required. This could help overcome longstanding barriers that have limited the use of reinforcement learning in industrial environments due to concerns over speed and data demands.
The work builds on research that began in 2020 through the European Interreg project KI-Net. Since 2022, development has continued within JRZ ISIA with support from industrial partners including B&R and COPA-DATA.
The patent filing highlights ongoing collaboration between academic institutions and industry as companies seek new technologies to improve efficiency and sustainability in industrial automation.
Source: Information based on an official announcement issued by ABB’s Machine Automation division (B&R)
Salzburg University and ABB’s Machine Automation Division (B&R) Collaborate to Advance AI-Enabled Energy Optimization in Industrial Motion Control | B&R Industrial Automation
