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The neural networks identification model is developed on the basis of the force analysis of magnetic bearing spindle, which reflects the nonlinear delay character between inputs and outputs system. This network is able to converge quickly in 5 training steps. The mean square error value reduces to 3.495e-006 in 50 steps. Inspection shows that the neural networks DTNN identification model can fit the...
There has been an increasing interest in conducting polymers, especially polypyrrole (PPy), as potential actuators for many cutting edge applications including micromanipulation and biomedical devices. Their performance needs to be assessed in terms of force and displacement outputs before they can be employed in practical devices. As part of an ongoing project to develop a robotic gripper for micromanipulation/fabrication...
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