Saleh Mehara

Work place: Industrial Electrical and Electronic Engineering SanatkadeheSabze Pasargad. CO (S.S.P. Co), NO:16 , PO.Code

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Research Interests: Artificial Intelligence, Robotics, Process Control System

Biography

Saleh Mehara is an electrical electronic researcher of research and development company SSP. Co. His main areas of research interests are nonlinear control, artificial control system and robotics.

Author Articles
GDO Artificial Intelligence-Based Switching PID Baseline Feedback Linearization Method: Controlled PUMA Workspace

By Farzin Piltan Reza Bayat Saleh Mehara Javad Meigolinedjad

DOI: https://doi.org/10.5815/ijieeb.2012.05.03, Pub. Date: 8 Oct. 2012

Congetive method is used in this research to create portfilo of movement robot manipulator. Gradient descent (GD) artificial intelligence based switching feedback linearization controller was used and robot's postures and trajectory were expected in MATLAB/SIMULINK environment. Feedback linearization controller (CTC) is an influential nonlinear controller to certain systems which it is based on feedback linearization and computes the required torques using the nonlinear feedback control law in certain systems. Practically a large amount of systems have uncertainties accordingly this method has a challenge. Switching feedback linearization controller is a significant combination nonlinear stable-robust controller under condition of partly uncertain dynamic parameters of system. This technique is used to control of highly nonlinear systems especially in nonlinear time varient nonlinear dynamic system. To increase the stability and robustness with regards to improve the robustness switching methodology is applied to feedback linearization controller. Lyapunov stability is proved in proposed controller based on switching function. To compensate for the dependence on switching parameters baseline methodology is used.The nonlinear model dynamic formulation problem in uncertain system can be solved by using artificial intelligence theorem. Fuzzy logic theory is used to estimate the system dynamic. Forward kinematics implemented the manipulator's movements. Results validated the robot's range of possible postures and trajectories

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