Coupled dynamic modeling, identification and experimental validation of a hydraulically driven soft robotic arm

Unlocking the high-performance potential of Hydraulically-Driven Soft Robotic Arms (HDSRAs) requires computationally tractable dynamic models that are both physically faithful and rigorously validated, a combination that remains a critical challenge. This paper addresses this gap by presenting a systematic framework for the modeling, identification, and multi-faceted validation of such systems. Central to the framework is an enhanced coupled dynamic model incorporating often-neglected physical phenomena, including stiffness coupling, Rayleigh damping, and pressure-dependent hydraulics. The framework’s value is then established through a cohesive suite of four targeted experimental studies. An ablation study first quantitatively confirms the necessity of each model enhancement. A comparative analysis subsequently demonstrates the model’s superior accuracy against representative existing methods. A model-based feedforward control experiment then proves the model’s practical utility by significantly improving trajectory tracking performance. Finally, a generalization study on a more complex tri-chamber arm confirms the framework’s scalability. This work delivers not just a model, but a fully validated, high-fidelity “digital twin” that provides a solid foundation for designing high-performance controllers for a broad class of HDSRAs.