Design Modified Fuzzy Hybrid Technique: Tuning By GDO

Design Modified Fuzzy Hybrid Technique: Tuning By GDO

Автор: Mohammad Shamsodini, Farzin Piltan, Mahdi Jafari, Omid reza Sadrnia, Omid Mahmoudi

Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs

Статья в выпуске: 8 vol.5, 2013 года.

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The Proportional Integral Derivative (PID) Fuzzy hybrid (switching mode computed torque sliding mode) Controller is presented in this research. The popularity of PID FHC controllers can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. The process of setting of PID FHC controller can be determined as an optimization task. Over the years, use of intelligent strategies for tuning of these controllers has been growing. Biologically inspired evolutionary strategies have gained importance over other strategies because of their consistent performance over wide range of process models and their flexibility. This paper analyses the manual tuning techniques and compares the same with Gradient Descent tuning methods for tuning PID FHC controllers for flexible robot manipulator system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.

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PID fuzzy control, Sliding mode control, computed torque methodology, robust controller, Gradient descent optimization, flexible robot manipulator

Короткий адрес: https://sciup.org/15014577

IDR: 15014577

Список литературы Design Modified Fuzzy Hybrid Technique: Tuning By GDO

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  • Farzin Piltan, Sadeq Allahdadi, Mohammad A.Bairami & Hajar Nasiri, “Design Auto Adjust Sliding Surface Slope: Applied to Robot Manipulator”, International Journal of Robotics and Automation, 3 (1):27-44, 2011.
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  • Farzin Piltan, Sadeq Allahdadi, Mohammad A.Bairami & Hajar Nasiri, “Design Auto Adjust Sliding Surface Slope: Applied to Robot Manipulator”, International Journal of Robotics and Automation, 3 (1):27-44, 2012.
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  • Farzin Piltan, M.R. Rashidian, M. Shamsodini and S. Allahdadi. ” Effect of Rule Base on the Fuzzy-Based Tuning Fuzzy Sliding Mode Controller: Applied to 2nd Order Nonlinear System”, International Journal of Advanced Science and Technology, 46:39-70, 2012.
  • Farzin Piltan, A. Jahed, H. Rezaie and B. Boroomand. ” Methodology of Robust Linear On-line High Speed Tuning for Stable Sliding Mode Controller: Applied to Nonlinear System”, International Journal of Control and Automation, 5(3): 217-236, 2012.
  • Farzin Piltan, R. Bayat, S. Mehara and J. Meigolinedjad. ”GDO Artificial Intelligence-Based Switching PID Baseline Feedback Linearization Method: Controlled PUMA Workspace”, International Journal of Information Engineering and Electronic Business, 5: 17-26, 2012.
  • Farzin Piltan, B. Boroomand, A. Jahed and H. Rezaie. ”Performance-Based Adaptive Gradient Descent Optimal Coefficient Fuzzy Sliding Mode Methodology”, International Journal of Intelligent Systems and Applications, 11: 40-52 2012.
  • Farzin Piltan, S. Mehrara, R. Bayat and S. Rahmdel. ” Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology”, International Journal of Hybrid Information Technology, 5(4):41-54, 2012.
  • AH Aryanfar, MR Khammar, Farzin Piltan, “Design a robust self-tuning fuzzy sliding mode control for second order systems”, International Journal of Engineering Science REsearch, 3(4): 711-717, 2012.
  • Farzin Piltan, Shahnaz Tayebi Haghighi, “Design Gradient Descent Optimal Sliding Mode Control of Continuum Robots”, International Journal of Robotics and Automation, 1(4): 175-189, 2012.
  • Farzin Piltan, A. Nabaee, M.M. Ebrahimi, M. Bazregar, “Design Robust Fuzzy Sliding Mode Control Technique for Robot Manipulator Systems with Modeling Uncertainties”, International Journal of Information Technology and Computer Science, 5(8), 2013.
  • Farzin Piltan, M. Akbari, M. Piran , M. Bazregar. ”Design Model Free Switching Gain Scheduling Baseline Controller with Application to Automotive Engine”, International Journal of Information Technology and Computer Science, 01:65-73, 2013.
  • Farzin Piltan, M. Piran , M. Bazregar, M. Akbari, “Design High Impact Fuzzy Baseline Variable Structure Methodology to Artificial Adjust Fuel Ratio”, International Journal of Intelligent Systems and Applications, 02: 59-70, 2013.
  • Farzin Piltan, M. Mansoorzadeh, M. Akbari, S. Zare, F. ShahryarZadeh “Management of Environmental Pollution by Intelligent Control of Fuel in an Internal Combustion Engine“ Global Journal of Biodiversity Science And Management, 3(1), 2013.
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