Generalized Dynamic Fuzzy Neural Network-Based Tracking Control of Robot Manipulators

Authors:
Qiguang Zhu;Hongrui Wang;Jinzhuang Xiao
Affiliations:
Institute of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China;Institute of Electronic and Information Engineering, Hebei University, Baoding 071002, China;Institute of Electronic and Information Engineering, Hebei University, Baoding 071002, China
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Year:
2007

Citing 2
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Abstract

A robust adaptive control based on generalized dynamic fuzzy neural network (GD-FNN) is presented for robot manipulators. Fuzzy control rules can be generated or deleted automatically according to their significance to the control system, and no predefined fuzzy rules are required. Being use of radial basis function neural network (RBFNN) the learning speed is very fast. The asymptotic stability of the control system is established using Lyapunov theorem. Simulations are given for a two-link robot in the end of paper, and validated the control arithmetic.