Title :
New neural networks for adaptive control of robot manipulators
Author_Institution :
Div. of Mech. Eng., Erciyes Univ., Kayseri, Turkey
Abstract :
The use of neural network for controlling of a robot is discussed in this paper. A new neural network is proposed to model and control a robot. The proposed network is a modification of the original Elman network. Also, a new control system design based on the neural network model of the robot dynamics for trajectory tracking control is studied. The proposed control system consists of a neural controller, a neural model of the robot and a P-controller. Simulation results show the effectiveness of using the neural network model in the design of the robot controller
Keywords :
adaptive control; learning (artificial intelligence); manipulator dynamics; neurocontrollers; position control; recurrent neural nets; Elman network; P-controller; adaptive control; control system; neural controller; neural model; robot dynamics; robot manipulators; trajectory tracking control; Adaptive control; Automatic control; Control systems; Equations; Manipulator dynamics; Motion control; Neural networks; Nonlinear control systems; Robot control; Robotics and automation;
Conference_Titel :
Neural Networks,1997., International Conference on
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-4122-8
DOI :
10.1109/ICNN.1997.614156
