Adaptive Finite-Time Convergence Fuzzy ARX-Laguerre System Estimation

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Farzin Piltan 1 Shahnaz TayebiHaghighi 2 Amirzubir Sahamijoo 2 Hossein Rashidi Bod 2 Somayeh Jowkar 2,3 Jong-Myon Kim 1,*

1. School of Electrical, Electronic, and Computer Engineering, University of Ulsan, Ulsan, South Korea

2. Control and Robotic Lab, IRAN SSP Research and Development Center, Shiraz, Iran

3. Department of Information Technology, Faculty of Computer Engineering, Ateneo De Manila University, Manila, Philippines

* Corresponding author.


Received: 22 Oct. 2018 / Revised: 15 Dec. 2018 / Accepted: 5 Jan. 2019 / Published: 8 May 2019

Index Terms

Finite-time, robot manipulator, fuzzy logic inverse dynamic modeling, parameter estimation, unknown dynamic parameters


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.

Cite This Paper

Farzin Piltan, Shahnaz TayebiHaghighi, Amirzubir Sahamijoo, Hossein Rashidi Bod, Somayeh Jowkar, Jong-Myon Kim, "Adaptive Finite-Time Convergence Fuzzy ARX-Laguerre System Estimation", International Journal of Intelligent Systems and Applications(IJISA), Vol.11, No.5, pp.27-35, 2019. DOI:10.5815/ijisa.2019.05.04


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