Fast sensorless collision detection for resource-constrained pmsm controllers using an FFRLS-based method.

Area of Science:

• Electrical Engineering
• Control Systems
• Robotics

Background:

• Collision detection is crucial for protecting machinery and ensuring safety in automated systems.
• Existing methods often require complex computations or external sensors, limiting their use in resource-constrained environments.
• Permanent-magnet synchronous motors (PMSMs) are widely used in industrial applications, necessitating efficient collision detection solutions.

Purpose of the Study:

• To develop a low-complexity, fast, and sensorless collision detection algorithm for PMSMs.
• To enable reliable collision detection in embedded controllers with limited computational resources.
• To achieve rapid detection of collisions under various operating conditions.

Main Methods:

• Utilizing a forgetting-factor recursive least-squares (FFRLS) estimator to estimate load torque from motor motion equations.
• Monitoring abrupt changes in a processed load-torque metric for collision event identification.
• Designing the algorithm to avoid high-order matrix operations and external sensor integration.

Main Results:

• The proposed method demonstrated fast and repeatable collision detection performance.
• Experimental validation confirmed effectiveness under constant speed, acceleration, and time-varying load conditions.
• The algorithm achieved a practical balance between computational cost and detection reliability.

Conclusions:

• The FFRLS-based sensorless collision detection method offers an effective solution for PMSMs.
• The approach is well-suited for resource-constrained embedded motor drives.
• This technique enhances the safety and robustness of automated systems utilizing PMSMs.