of Hybrid Machine Based on RBF Neural Network
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    Abstract:

    The precision of trajectory tracking of hybrid machine was debased because of velocity fluctuation in constant velocity motor and uncertainties in the system. The strategy for control servo motor grounded on tracking the motion was proposed, to compensate the velocity fluctuation of constant velocity motor. Considering the uncertainties of the system, an adaptive sliding mode controller based on RBF neural network was designed for trajectory tracking of hybrid machine. The sum of uncertainties of the system was compensated by control gain with RBF neural network, and the output weight of in network was adjusted by adaptive algorithm. The simulation result indicated the robustness and effectiveness of the controller.

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