Robust adaptive control
Stabilization of Nonlinear Uncertain Systems
Stabilization of Nonlinear Uncertain Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Adaptive Neural Network Control of Robotic Manipulators
Adaptive Neural Network Control of Robotic Manipulators
Stable Adaptive Neural Network Control
Stable Adaptive Neural Network Control
Sliding Mode Adaptive Neural-Network Control for Nonholonomic Mobile Modular Manipulators
Journal of Intelligent and Robotic Systems
Information Sciences: an International Journal
Asymptotic Adaptive Neural Network Tracking Control of Nonholonomic Mobile Robot Formations
Journal of Intelligent and Robotic Systems
Dual adaptive dynamic control of mobile robots using neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Neural Computing and Applications - Special Issue on Theory and applications of swarm intelligence
Adaptive control for mobile robot using wavelet networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Control of a nonholonomic mobile robot using neural networks
IEEE Transactions on Neural Networks
High-order neural network structures for identification of dynamical systems
IEEE Transactions on Neural Networks
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In this paper, the global tracking control problem for a class of wheeled mobile robots is considered and a new adaptive position tracking control scheme is proposed where radial basis function (RBF) neural network (NN) is utilized to model the uncertainty. The feedback compensation scheme is obtained, where the information of reference position and real position of robot are both used as the NN input. Compered with the existing results, the main advantage is that the global stability of the closed-loop system can be ensured and the NN approximation domain can be determined based on the reference signal a prior. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed control scheme.