Title :
A design of prefilter type compensatory controller for robot manipulator using modified chaotic neural networks
Author :
Kim, Sang-Hee ; Hong, Su-Dong ; Chai, Chang-Hyun ; Park, Won-Woo
Author_Institution :
Sch. of Electron. Eng., Kumoh Nat. of Tech., South Korea
Abstract :
This paper presents a prefilter type compensatory controller for robotic manipulator using modified chaotic neural networks (MCNNs). The structure of the proposed prefilter type compensatory controller consists of two MCNNs that compensate position and velocity error of the proportional-derivative (PD) controller. The simulation results show the excellent performance on convergence and fast learning comparing with adaptive recurrent neural networks (RNNs) controller that is composed of a PD controller and RNNs in parallel
Keywords :
compensation; convergence; learning (artificial intelligence); manipulator dynamics; neurocontrollers; position control; two-term control; velocity control; PD controller; chaotic neural networks; compensation; compensatory controller; convergence; fast learning; position control; prefilter; robot manipulator; velocity control; Chaos; Convergence; Error correction; Manipulators; Neural networks; PD control; Proportional control; Recurrent neural networks; Robot control; Velocity control;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.832694
