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.
Dettaglio pubblicazione
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
ISBN: 978-88-945805-3-2
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