Simulation of a pneumatic hand crane for work support was developed for system design. The crane's mathematical model consists of a pneumatic cylinder model, a crane link model, and a controller that includes a human model to passively operate the hand crane by operating force. The human model's inverse system learns using a neural network. The feasibility of the simulation was demonstrated in comparison with measurement results from operating force and acceleration.
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