Robot trajectory Tracking with Adaptive RBFNN-Based fuzzy sliding Mode Control

Abstract

Due to computational burden and dynamic uncertainty, the classical model-based control approaches are hard to be implemented in the multivariable robotic systems. In this paper, a model-free fuzzy sliding mode control based on neural network is proposed. In classical sliding mode controllers, system dynamics and system parameters are required to compute the… (More)
DOI: 10.5755/j01.itc.40.2.430

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Cite this paper

@article{Ak2011RobotTT, title={Robot trajectory Tracking with Adaptive RBFNN-Based fuzzy sliding Mode Control}, author={Ayca Gokhan Ak and Galip Cansever and Akin Delibasi}, journal={ITC}, year={2011}, volume={40}, pages={151-156} }