Feedforward Pressure-Regulated Position Control of Soft Ballooning Actuators Using a Modified Prandtl–Ishlinskii Model

Abstract

Thanks to their compliance and adaptability, soft actuators are promising devices for medical applications and the exploration of unstructured environment. However, their nonlinear behaviour, including strong hysteresis effects, presents challenges for accurate position control. This work investigates two data-driven feedforward control strategies for controlling the position of a Hyper-Elastic Ballooning Membrane Actuator (HBMA): a baseline single polynomial fit model and a hysteresis-aware Modified Prandtl-Ishlinskii (MPI) model. Comparative experiments demonstrate that hysteresis-aware control substantially improves accuracy. Specifically, incorporating hysteresis improved overall accuracy by 71% when the HBMA was inflated up to 20.5 mm. During partial inflation-deflation cycles, the MPI controller achieved a mean error of 0.685 mm, corresponding to 9.8% of the 7 mm displacement range. These results highlight the limitations of using feedforward control alone in soft robotic actuation while emphasising the benefits of hysteresis-aware modelling. The findings contribute to the ongoing effort to develop effective control strategies for soft robotic systems.