Adaptive finite-time convergence fuzzy ARX-laguerre system estimation
Автор: Farzin Piltan, Shahnaz TayebiHaghighi, Amirzubir Sahamijoo, Hossein Rashidi Bod, Somayeh Jowkar, Jong-Myon Kim
Журнал: International Journal of Intelligent Systems and Applications @ijisa
Статья в выпуске: 5 vol.11, 2019 года.
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Convergence speed for system identification and estimation is a popular topic for determining the kinematics and dynamic identification/estimation of the parameters of robot manipulators. In this paper, adaptive fuzzy inverse dynamic system estimation is used to improve robust modeling, especially for a serial links robot manipulator. The Lyapunov technique is used to analyze the convergence rate of the tracking error and increase the accuracy response of the parameter estimation. Performance of robot estimation is conducted, and the results show fast convergence of the proposed finite time technique for a 6-DOF robot manipulator.
Finite-time, robot manipulator, fuzzy logic inverse dynamic modeling, parameter estimation, unknown dynamic parameters
Короткий адрес: https://sciup.org/15016593
IDR: 15016593 | DOI: 10.5815/ijisa.2019.05.04
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