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2022, 2022 I-RIM Conferen, Pages 151-152

Regulation by Iterative Learning in Continuum Soft Robots (04b Atto di convegno in volume)

Montagna Marco, Pustina Pietro, DE LUCA Alessandro

The dynamic uncertainties and disturbances characterizing continuum soft robots call for the derivation of simple and possibly information-free controllers. We propose an iterative learning control law for shape regulation of continuum soft robots consisting of a PD action and a feedforward term, updated to learn the potential forces at the target configuration. We prove that the regulator achieves global asymptotic stabilization of the closed-loop system to the desired set-point. Simulation results validate the proposed control law.
ISBN: 978-88-945805-3-2
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