Jong-Myon Kim

Work place: School of Electrical, Electronic, and Computer Engineering, University of Ulsan, Ulsan, South Korea



Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Embedded System, Processor Design, Systems Architecture, Parallel Computing


Jong-Myon Kim (M'05) received his B.S. degree in electrical engineering from Myongji University, Yongin, South Korea in 1995, M.S. degree in electrical and computer engineering from the University of Florida, Gainesville, FL, USA in 2000, and Ph.D. degree in electrical and computer engineering from the Georgia Institute of Technology, Atlanta, GA, USA in 2005. He is currently a professor with the Department of IT Convergence and Vice President of the Foundation for Industry Cooperation at the University of Ulsan, Ulsan, South Korea. His research interests include multimedia-specific processor architecture, fault diagnosis and condition monitoring, parallel processing, and embedded systems. Dr. Kim is a member of the IEEE Industrial Electronics Society.

Author Articles
Adaptive Finite-Time Convergence Fuzzy ARX-Laguerre System Estimation

By Farzin Piltan Shahnaz TayebiHaghighi Amirzubir Sahamijoo Hossein Rashidi Bod Somayeh Jowkar Jong-Myon Kim

DOI:, Pub. Date: 8 May 2019

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.

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Control of an Uncertain Robot Manipulator Using an Observation-based Modified Fuzzy Sliding Mode Controller

By Shahnaz TayebiHaghighi Farzin Piltan Jong-Myon Kim

DOI:, Pub. Date: 8 Mar. 2018

The main contribution of this paper is the design of a robust model reference fuzzy sliding mode observation technique to control multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. A fuzzy sliding mode controller was used in this study to control the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, chattering phenomenon, and error convergence under uncertain conditions, the proposed sliding mode observer was applied to the fuzzy sliding mode controller. This theory was applied to a six-degrees-of-freedom (DOF) PUMA robot manipulator to verify the power of the proposed method.

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Other Articles