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This paper introduces a control-oriented data-driven modeling and control framework for soft pneumatic actuators, addressing the challenges posed by their nonlinear dynamics. By decomposing actuator behavior into a nonlinear static equilibrium model and a linear residual dynamics model using Extended Dynamic Mode Decomposition with control (EDMDc), the authors achieve precise trajectory tracking and stability analysis. Experimental results show that the framework can maintain low root mean square error (RMSE) in tracking and ensure stability during dynamic operations, validating its practical application in real-time scenarios.
Achieving sub-1 mm tracking accuracy in soft pneumatic actuators while enabling real-time obstacle avoidance could redefine standards in soft robotics control.
Soft pneumatic actuators offer inherent compliance and safe interaction but remain difficult to model and control because of their highly nonlinear, distributed dynamics. We present a control-oriented data-driven modeling and control framework that decomposes actuator behavior into a nonlinear static equilibrium model and a linear residual dynamics model identified using Extended Dynamic Mode Decomposition with control (EDMDc). This representation enables feedforward compensation, task-space feedback control, and local closed-loop stability analysis through an augmented linear model. Experiments achieve approximately 1 mm root mean square error (RMSE) during low-speed (approximately 10 mm/s) trajectory tracking and below 10 mm RMSE at higher speeds (approximately 100 mm/s). The framework further achieves stable tracking of highly dynamic user-generated references with peak accelerations exceeding 25 m/s^2 while simultaneously performing real-time obstacle avoidance. Finally, the proposed stability analysis is experimentally validated by accurately predicting stable, marginal, and unstable operating regimes. These results demonstrate that structured, control-oriented learning provides an accurate and practical framework for soft actuator control.
