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Author Gao, Yang ♦ Er, Meng Joo ♦ Mastorakis, Nikos ♦ Leithead, W. E. ♦ Leith, D. J.
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Trajectory Tracking ♦ Fuzzy Neural Controller ♦ Fuzzy Neural Network ♦ Adaptive Capability ♦ Two-link Robot Manipulator ♦ Intelligent Control Scheme ♦ Dynamic Structure ♦ First Portion ♦ Robot Model ♦ Robot Manipulator ♦ Short D-fnns ♦ Computer Simulation ♦ Trajectory Control ♦ High Performance ♦ Second Portion ♦ Model Learning ♦ New Control Scheme ♦ Time-varying Condition ♦ On-line Weight Adjustment
Abstract Abstract — This paper presents a new control scheme utilizing fuzzy neural networks for trajectory control of robot manipulators. The adaptive capability of the fuzzy neural controller ensures that high performance can be achieved and maintained under time-varying conditions. This intelligent control scheme consists of two portions. In the first portion, the fuzzy neural networks with dynamic structure, in short D-FNNs, are constructed to estimate dynamics of the robot model. The second portion is the fuzzy neural controller, which is built based on model learning and on-line weight adjustment. Computer simulations of a two-link robot manipulator demonstrate the effectiveness and efficiency of the proposed scheme. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article