Energy-Based Auto-Tuning of Velocity Flow Controller for Exoskeleton-User Speed Synchronization
Lyndon Tang, Bhavya Giri Goswami, Atusa Ghorbani Siavashani, John McPhee, Rezvan Nasiri, Arash Arami
AI summary
Problem
Poorly tuned Velocity Flow Field controllers create a viscous damping effect that resists user motion and diminishes walking agency. This study addresses how to automatically synchronize exoskeleton assistance with the user's natural speed and effort.
Approach
The authors decompose the control law to eliminate the damping term and implement an online optimization algorithm that continuously adjusts the controller's speed gain to minimize the average mechanical work exchanged per step.
Key results
- Tracks dynamic walking speed changes in real time
- Reduces energy absorption by 0.589 J/step at fast speeds
- Decreases user-controller disagreement and increases user agency
- Maintains near-zero assistive energy transfer across varying speeds
Why it matters
Provides a practical, energy-driven coordination mechanism for personalized and real-time exoskeleton assistance in gait rehabilitation.
Abstract
The Velocity Flow Field (VFF) lower-limb ex- oskeleton controller is widely applicable for gait rehabilitation because it provides the user with considerable agency over their gait; however, previous studies reported the feeling of “walking through water”, and resistance to the user’s efforts. In this work, a mathematical explanation for the viscous damping behaviour when users deviate from the reference trajectory, is presented. The controller was corrected and an adaptation law is proposed that synchronizes the speed gain with the user’s current walking speed by minimizing the average mechanical work transferred between the user and the exoskeleton per step. Experiments comparing a fixed and adaptive controller with 12 participants walking at 0.4 ± 0.1 body length/s on a treadmill showed that the adaptive controller tracks changes in walking speed, while reducing the energy absorbed by 0.589±0.126 J step compared to the fixed controller at the fastest walking speed. Analysis of changes in muscle effort and interaction torques with a human-exoskeleton interaction portrait showed that for most participants, the adaptive controller at medium and fast speeds substantially reduced user-controller disagreement and increased user agency over the walking motion. These positive results suggest that optimizing the energy supplied per step can serve as an effective coordination mechanism, enabling personalized and real-time adjustments of walking speed between the user and the exoskeleton.