Adaptive Robust Control for Rotation Tracking of a Soft Rotary Actuator with Hysteresis Compensation
Young Min Lee, Yeoil Yun, Hyungpil Moon, Hyouk Ryeol Choi, Yong Seok Ihn, Ja Choon Koo
AI summary
Problem
Precise control of soft pneumatic actuators is hindered by large internal volume variations during actuation, which are often ignored in conventional fixed-volume models, leading to unmodeled dynamics and energy inefficiency.
Approach
The authors propose an adaptive robust control framework that integrates a Modified Prandtl-Ishlinskii hysteresis compensator with a real-time internal volume estimator using an embedded Time-of-Flight sensor to dynamically adjust valve control inputs.
Key results
- 25.2% reduction in PWM control effort under baseline conditions
- 50.6% reduction in control effort under 0.9 Nm external load
- Maintained robust trajectory tracking despite direct ToF sensor disturbance
- Superior tracking stability compared to conventional fixed-volume models
Why it matters
Provides a generalizable, energy-efficient control strategy for soft robotic systems where large geometric deformations critically impact pneumatic dynamics.
Abstract
Precise control of soft pneumatic actuators is im- peded by significant nonlinearities, particularly large internal volume variations during actuation—a factor often overlooked in conventional modeling. This paper proposes an adaptive robust control (ARC) framework designed for high-performance, energy-efficient control of soft actuators with non-negligible volume dynamics. The framework integrates a Modified Prandtl- Ishlinskii (MPI) model for hysteresis compensation with a real- time volume estimator using an internal Time-of-Flight (ToF) sensor. The ARC law then systematically handles uncertainties from both valve parameter variations and the volume estimation process. Experimental validation, through direct comparison with a conventional fixed-volume model, demonstrates that this volume-aware approach achieves robust trajectory tracking with significantly reduced control effort and energy consumption. This work establishes that explicitly modeling internal volume dynamics is crucial for developing high-performance control systems for a broad class of soft pneumatic actuators.