Grey-Prediction Self-Organizing Fuzzy Controller for Robotic Manipulators

• Main Authors: YANG, JING-XING, 楊景翔
• Other Authors: LIAN, RUEY-JING
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/19075294887827586972

碩士 === 華夏科技大學 === 智慧型機器人研究所 === 105 === A robotic manipulator is one of complicated and nonlinear multiple-input multipleoutput (MIMO) systems. It is difficulty to design model-based controllers for the control of robotic manipulators. In order to solve the problem, this study employed model-free self-organizing fuzzy controller (SOFC) to control the robotic manipulator. However, the parameters of the SOFC are fixed once the parameters decided. The system will cause easily oscillation or instability due to inappropriate parameters chosen for the design of the SOFC. In order to overcome the problem, this study developed a grey-prediction self-organizing fuzzy controller (GPSOFC) for the control of robotic manipulators. The GPSOFC applies the grey-prediction algorithm to predict the next-step error and error change of the system. This eliminates the effect of the inappropriate parameters chosen of the SOFC to enhance the control performance of the system. Experimental results demonstrated that the control performance of the SPSOFC is superior to that of the SOFC as well as fuzzy logic controller for robotic motion control.