Neural network controllers for robot manipulators application of damping neurons

^_This paper presents an effective adaptive neural network feedback controller for force control of robot manipulators in an unknown environment by applying damping neurons which possess elastic-viscous properties. The unexpected overshooting and oscillation caused by the unknown and/or unmodeled dynamics of a robot manipulator and an environment can be decreased efficiently by the effect of the proposed damping neurons. Furthermore, a fuzzy controlled evaluation function is applied for the learning of the proposed neural network controller, so that the controller is able to adapt to the unknown environment more effectively. The effectiveness of the proposed neural network controller is evaluated by experiment with a 3 d.o.f. direct-drive planar robot manipulator.