Iterative Learning Control Strategy for a Furuta Pendulum System with Variable-Order Linearization
Résumé
We consider Iterative Learning Control for the Furuta Pendulum nonlinear mechanical system, where the goal is to learn the input torque such that the pendulum angle follows a reference. We show that the linearization of the considered system is of variable trajectorydependent order and thus some existing solutions do not apply. We propose a novel method based on the observability matrix inversion allowing to deal with the variable-order minimum realization. The applicability of the proposed method is illustrated with simulations.
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Binz Aranovskiy 2021 Iterative Learning Control Strategy for a Furuta Pendulum System with Variable-Order Linearization.pdf (606.6 Ko)
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