Somayeh Jowkar

Work place: Control and Robotic Lab, IRAN SSP Research and Development Center, Shiraz, Iran



Research Interests:


Somayeh Jowkar is a research associate at the IRANSSP research and development center.

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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A Novel Intelligent ARX-Laguerre Distillation Column Estimation Technique

By Farzin Piltan Shahnaz TayebiHaghighi Somayeh Jowkar Hossein Rashidi Bod Amirzubir Sahamijoo Jeong-Seok Heo

DOI:, Pub. Date: 8 Apr. 2019

In practical applications, modeling of real systems with unknown parameters such as distillation columns are typically complex. To address issues with distillation column estimation, the system is identified by a proposed intelligent, auto-regressive, exogenous-Laguerre (AI-ARX-Laguerre) technique. In this method, an intelligent technique is introduced for data-driven identiļ¬cation of the distillation column. The Laguerre method is used for the removal of input/output noise and decreases the system complexity. The fuzzy logic method is proposed to reduce the system’s estimation error and to accurately optimize the ARX-Laguerre parameters. The proposed method outperforms the ARX and ARX-Laguerre technique by achieving average estimation accuracy improvements of 16% and 9%, respectively.

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Other Articles