Abstract
A stable discrete-time adaptive tracking controller using neuro–fuzzy (NF) dynamic inversion is proposed for a robotic manipulator with its dynamics approximated by a dynamic T-S fuzzy model. NF dynamic inversion is used to compensate for the robot inverse dynamics. By assigning the dynamics of the Dynamic NF (DNF) system, the dynamic performance of the robot control system can be guaranteed in the initial control stage. The discrete-time adaptive control composed of NF dynamic inversion and NF variable structure control (NF-VSC) is developed to stabilize the closed-loop system and ensure the high-quality tracking. The system stability and the convergence of tracking errors are guaranteed and effectiveness of the proposed control approach. is verified.
This work was jointly supported by the National Excellent Doctoral Dissertation Foundation (No:200041), National Natural Science Foundation of China (No: 60474025, 90405017) and National Key Project for Basic Research of China (No: G2002cb312205)
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© 2005 Springer-Verlag Berlin Heidelberg
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Sun, F., Tang, Y., Li, L., Yin, Z. (2005). Discrete-Time Adaptive Controller Design for Robotic Manipulators via Neuro-fuzzy Dynamic Inversion. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_32
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DOI: https://doi.org/10.1007/11427469_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25914-5
Online ISBN: 978-3-540-32069-2
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