Application of a general learning algorithm to the control of robotic manipulators
International Journal of Robotics Research
Using backpropagation with temporal windows to learn the dynamics of the CMU direct-drive arm II
Advances in neural information processing systems 1
Supervised learning and systems with excess degrees of freedom
Supervised learning and systems with excess degrees of freedom
Brief Adaptive motion control using neural network approximations
Automatica (Journal of IFAC)
Technical Communique: A combined PID/adaptive controller for a class of nonlinear systems
Automatica (Journal of IFAC)
IEEE Transactions on Neural Networks
On adaptive trajectory tracking of a robot manipulator using inversion of its neural emulator
IEEE Transactions on Neural Networks
Robust neural-network control of rigid-link electrically driven robots
IEEE Transactions on Neural Networks
Gaussian networks for direct adaptive control
IEEE Transactions on Neural Networks
Neural net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
A Preliminar Analysis of CO2RBFN in Imbalanced Problems
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Expert Systems with Applications: An International Journal
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets
Pattern Recognition Letters
Control of robot manipulators in task-space under uncertainties using neural network
International Journal of Intelligent Engineering Informatics
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In this article, an adaptive neural network algorithm is developed for control issue of rigid-link electrically-driven (RLED) robot systems. First, an virtual control algorithm is designed to deal with the mechanical dynamics. Next, an actual neural network controller is used to handle the uncertainty in the mechanical and electrical dynamics. The stability is guaranteed by using a rigid stability proof. Finally, a simulation is given to show the effectiveness of the proposed algorithm.