Abstract: Imitation Learning (IL) is a promising paradigm for learning dynamic manipulation of deformable objects since it does not depend on difficult-to-create accurate simulations of such objects.
Abstract: This paper investigates the neural network-based event-triggered attack-compensation control problem of T-S fuzzy systems in the presence of actuator attacks. In order to enhance the ...
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