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Creators/Authors contains: "Volchko, Angella"

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  1. Soft robots require a complimentary control architecture to support their inherent compliance and versatility. This work presents a framework to control soft-robotic systems systematically and effectively. The data-driven model-based approach developed here makes use of Dynamic Mode Decomposition with control (DMDc) and standard controller synthesis techniques. These methods are implemented on a robotic arm driven by an antagonist pair of Hydraulically Amplified Self-Healing Electrostatic (HASEL) actuators. The results demonstrate excellent tracking performance and disturbance rejection, achieving a steady state error under 0.25% in response to step inputs and maintaining a reference orientation within 0.5 degrees during loading and unloading. The procedure presented in this work can be extended to develop effective and robust controllers for other soft-actuated systems without knowledge of their dynamics a priori. 
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