Abstract
This paper proposes a fuzzy sliding mode controller with radial basis function neural network (RBFNN) for trajectory tracking of robot manipulator. The main problem of sliding mode controllers is that a whole knowledge of the system dynamics and system parameters is required to compute the equivalent control. In this paper, a RBFNN is proposed to compute the equivalent control. Computer simulations of three link robot manipulator for trajectory tracking indicate that the proposed method is a good candidate for trajectory control applications.
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© 2006 Springer-Verlag Berlin Heidelberg
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Ak, A.G., Cansever, G. (2006). Fuzzy Sliding Mode Controller with RBF Neural Network for Robotic Manipulator Trajectory Tracking. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Control and Automation. Lecture Notes in Control and Information Sciences, vol 344. Springer, Berlin, Heidelberg . https://doi.org/10.1007/978-3-540-37256-1_64
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DOI: https://doi.org/10.1007/978-3-540-37256-1_64
Publisher Name: Springer, Berlin, Heidelberg
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