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- W2328542372 abstract "In this paper, the nonlinear three-layer Neural Network using a dynamic back-propagation method which based on the output signals of the hybrid controller and past output information of the plant is proposed for the Cartesian position/force control of multi-DOF robots. The generalized delta law is used as a learning law to adjust the weights of the Neural Network at every sampling time in order to adapt to an unknown environment.Experiments were done with a 3-DOF Direct-Drive Planar Robot Manipulator. The proposed Neural Network Controller controls the position and the angle of the end-effector as well as the applied force to an unknown environment. The experimental results show the effectiveness and flexibility of the proposed Neural Network Position/Force Controller for Multi-DOF Robots." @default.
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- W2328542372 date "1995-01-01" @default.
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- W2328542372 title "Hybrid Control for an Unknown Environment Using Neural Networks." @default.
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- W2328542372 doi "https://doi.org/10.7210/jrsj.13.291" @default.
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