Abstract
With output redefinition of flexible-link manipulators an adaptive controller for tip tracking is presented based on radial basis function network (RBFN) and fuzzy system. The uniformly asymptotical stability (UAS) of control system is guaranteed by the Lyapunov analysis and the adaptive laws including the centers and widths of Gaussian functions and coefficients of Takagi-Sugeno (TS) consequences can make the tracking error converge to zero. For comparison purpose, an RBFN controller with fixed centers and widths is also designed. The simulation results show that with similar performances the proposed controller can give smoother input torques than the conventional RBFN one.
This work was jointly supported by the National Excellent Doctoral Dissertation Foundation (Grant No: 200041) and the National Key Project for Basic Research of China (Grant No: G2002cb312205).
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Tang, Y., Sun, F., Sun, Z. (2005). Tip Tracking of a Flexible-Link Manipulator with Radial Basis Function and Fuzzy System. 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_37
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DOI: https://doi.org/10.1007/11427469_37
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