Design and Implementation of Elastic Structure Preserving Vibration Suppression Control for Flexible Link Robots Using IMU Measurements
Alexander Kitzinger, Hubert Gattringer, Andreas Müller
AI summary
Problem
Lightweight industrial robots suffer from structural flexibility and vibrations, but existing vibration suppression methods are either too complex for industrial adoption or require unavailable link-side torque sensors.
Approach
The authors adapt the Elastic Structure Preserving control method to structurally elastic robots by fusing IMU measurements with an Extended Kalman Filter to estimate elastic states, enabling model-based damping injection via standard position-controlled servo drives.
Key results
- ESP control achieves superior vibration damping compared to flatness-based and standard PD controllers
- An IMU-based Extended Kalman Filter successfully estimates elastic link states without link-side torque sensors
- The control scheme maintains robust trajectory tracking and disturbance rejection under model uncertainties
- The method is successfully implemented on standard industrial hardware with straightforward modal tuning
Why it matters
Enables practical, high-performance vibration suppression for lightweight industrial robots using off-the-shelf sensors and controllers, bridging the gap between advanced control theory and industrial deployment.
Abstract
Elastic lightweight manipulators offer multiple benefits but suffer from increased structural flexibility, making them susceptible to vibrations and thus requiring dedicated control concepts for vibration suppression. Based on a lumped element model formulation, a method called elastic structure preserving (ESP) control is used for additional damping in- jection, while using standard PD motor position control. The control method is applied for the first time to a flexible link robot by combining it with a link-side IMU-based observer. It is demonstrated in an industrial context using a standard controller setup, enabling straightforward implementation on existing industrial robots. The novel ESP method is further compared to a flatness-based control approach and to standard PD motor control. Particular aspects of controller tuning are discussed. Both theoretical analysis and experimental evalua- tions are conducted to address trajectory tracking behavior, disturbance rejection, and robustness to model parameter uncertainties. Results based on end effector accelerations show that ESP achieves superior vibration damping, demonstrating its effectiveness for industrial lightweight robots.