Adaptive Neural Compensator for Robotic Systems Control

In the area of robotics systems, there are numerous applications where robots are expected to move rapidly from one place to another, or follow desired trajectories while maintaining good dynamic behavior. However, certain non-linearities, uncertainties in dynamics and external perturbations make th...

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Veröffentlicht in:	Revista IEEE América Latina 2019-04, Vol.17 (4), p.670-676
Hauptverfasser:	Gandolfo, Daniel Ceferino, Rossomando, Francisco Guido, Soria, Carlos Miguel, Carelli, Ricardo Oscar
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Adaptive control Adaptive systems artificial neural network Artificial neural networks Computer simulation Control stability Control systems Control theory Feedback control identification IEEE transactions Parameter robustness Parameter uncertainty PD control Robot arms Robot control robot manipulator Robotics Robots Stability analysis Torque Tracking errors
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