Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Robot Dynamics and Control
Robotics
A Stable Neuro-Adaptive Controller for Rigid Robot Manipulators
Journal of Intelligent and Robotic Systems
Neural network-based model reference adaptive control system
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An adaptive tracking controller using neural networks for a class of nonlinear systems
IEEE Transactions on Neural Networks
Output feedback control of nonlinear systems using RBF neural networks
IEEE Transactions on Neural Networks
Neural net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
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The aim of this paper is to investigate a control method for robotic agent, operating in ubiquitous network. It is difficult for people to fulfill their tasks under dynamically changing environment. Therefore, robotic agent performs tasks in stead of people. The ubiquitous network makes it possible to connect between robotic agent and people. Because robotic agent should fulfill tasks according to the received commands from people, the adaptive control method for the agent is needed in order to do the given tasks properly. This paper introduces an adaptive tracking control method for robotic agent based on the radial based functions network (RBFN). When some commands are received through networks, the proposed method can make robotic agent possible to perform tasks under dynamically changing environment. Experimental results show that the proposed control method based on RBFN is adaptable to the environment changes and is more robust than the conventional PID control method and the neuro-control method based on the multilayer perceptron.