Fuzzy neural controller for robot manipulator force control

Fuzzy-neural control, the combination of neural networks control which has a learning ability from experiments and fuzzy control which has an ability of dealing with human knowledge, has recently been studied in order to make up for each other´s weak points. In this paper, the fuzzy-neural controller is introduced for robot manipulator force control in an unknown environment. A robot manipulator force controller is designed using fuzzy logic in order to realize a human-like control and then modeled as a neural network to adjust membership functions and rules to achieve the desired force control. Errors between the desired force and measured force and momentum of robot manipulator are used as input signals of the controller. Simulation has done to confirm the effectiveness of the controller