Abstract
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.
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Sonmez, M., Kandilli, I., Yakut, M. (2006). Tracking Control Based on Neural Network for Robot Manipulator. In: Savacı, F.A. (eds) Artificial Intelligence and Neural Networks. TAINN 2005. Lecture Notes in Computer Science(), vol 3949. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11803089_6
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DOI: https://doi.org/10.1007/11803089_6
Publisher Name: Springer, Berlin, Heidelberg
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