Fundamentals of Robotics: Analysis and Control
Fundamentals of Robotics: Analysis and Control
Fundamentals for Control of Robotic Manipulators
Fundamentals for Control of Robotic Manipulators
Adaptive Control
Control of Robot Manipulators
Optimal design of CMAC neural-network controller for robotmanipulators
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Adaptive control of robot manipulator using fuzzy compensator
IEEE Transactions on Fuzzy Systems
Multilayer neural-net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
Neural-network-based robust fault diagnosis in robotic systems
IEEE Transactions on Neural Networks
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In this paper, a control algorithm based on neural networks is presented. This control algorithm has been applied to a robot arm which has a highly nonlinear structure. The model based approaches for robot control require high computational time and can result in a poor control performance, if the specific model structure selected does not properly reflect all the dynamics. The control technique proposed here has provided satisfactory results. A decentralized model has been assumed here where a controller is associated with each joint and a separate neural network is used to adjust the parameters of each controller. Neural networks have been used to adjust the parameters of the controllers, being the outputs of the neural networks, the control parameters.