A robust fuzzy logic controller for robot manipulators with uncertainties
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Neural and fuzzy robotic hand control
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Global asymptotic stability of a tracking sectorial fuzzy controller for robot manipulators
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive control of robot manipulator using fuzzy compensator
IEEE Transactions on Fuzzy Systems
Robust neural-network control of rigid-link electrically driven robots
IEEE Transactions on Neural Networks
Adaptive dynamic surface fuzzy control for a class of uncertain nonlinear systems
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
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This note presents a robust adaptive neural network (NN) control scheme for multi-fingered robot hand manipulation system in the constrained environment to achieve arbitrarily small motion and force tracking errors. The controllers consist of the model-based controller, the NN controller and the robust controller. The model-based controller deals with the nominal dynamics of the manipulation system. The NN handles the unstructured dynamics and external disturbances. The NN weights are tuned online, without the offline learning phase. The robust controller is introduced to compensate for the effects of residual uncertainties. An adaptive law is developed so that no priori knowledge of the bounds for residual uncertainties is required. Most importantly, the exponential convergence properties for motion and force tracking are achieved.