Adaptive control: stability, convergence, and robustness
Adaptive control: stability, convergence, and robustness
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Control Theory of Nonlinear Mechanical Systems
Control Theory of Nonlinear Mechanical Systems
Adaptive Neural Network Control of Robotic Manipulators
Adaptive Neural Network Control of Robotic Manipulators
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
Neural Network Control of Robot Manipulators
IEEE Expert: Intelligent Systems and Their Applications
Control of an object with parallel surfaces by a pair of finger robots without object sensing
IEEE Transactions on Robotics
Multilayer neural-net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
Neural networks for advanced control of robot manipulators
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Guest Editorial Special Issue on Neural Networks for Feedback Control Systems
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Neural net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
Design of robotic visual servo control based on neural network and genetic algorithm
International Journal of Automation and Computing
Short survey: Dual arm manipulation-A survey
Robotics and Autonomous Systems
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part II
Fuzzy Neural Network Control for Robot Manipulator Directly Driven by Switched Reluctance Motor
International Journal of Cognitive Informatics and Natural Intelligence
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It is interesting to observe that humans are able to manipulate an object easily and skillfully without the exact knowledge of the object, contact points, or kinematics of our fingers. However, research so far on multifingered robot control has assumed that the kinematics and contact points of the fingers are known exactly. In many applications of multifingered robot hands, the kinematics and contact points of the fingers are uncertain and structures of the Jacobian matrices are unknown. In this paper, we propose an adaptive neural network (NN) Jacobian controller for multifingered robot hand with uncertainties in kinematics, Jacobian matrices, and dynamics. It is shown that using NNs, the uniform ultimate boundedness of the position error can be achieved in the presence of the uncertainties. Simulation results are presented to illustrate the performance of the proposed controller.