Abstract
AbstractThis paper presents a novel model falsification strategy, based on Set-Valued Observers (SVOs) for uncertain Linear Parameter-Varying (LPV) systems. We show that, under mild conditions, the proposed methodology is able to select the correct model of the plant, among a set of plausible ones. The applicability of this approach is illustrated in simulation, resorting to a single-link robotic arm with a revolute elastic joint, with uncertain spring stiffness.
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