篇名 | Robot High Precision Trajectory Tracking Variable Domain Fuzzy Control |
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卷期 | 28:6 |
作者 | Min Wan 、 Ling-Zhi An 、 Deng-Zhou Hu 、 Hai-Feng Chen |
頁次 | 079-087 |
關鍵字 | fuzzy control 、 genetic algorithm 、 robot 、 trajectory tracking 、 variable universe 、 EI 、 MEDLINE 、 Scopus |
出刊日期 | 201712 |
DOI | 10.3966/199115992017122806007 |
In order to achieve the desired path of the robot, trajectory tracking of robot system is to follow a given trajectory change with each joint's controller output drive torque control of each joint position, velocity and other variables. However, the traditional design method of the controller was usually based on the controlled object model, but the various uncertain factors in the actual engineering will lead to the precise mathematical model of the robot can not be gained, therefore the traditional control method will be difficult to achieve the purpose of high precision control. The fuzzy controller does not need to know the exact mathematical, but the control precision of the fuzzy control is not high. In this paper, based on the fuzzy control of the robot, the paper introduces the variable universe theory, introduces the domain expansion factor in the input variables, and uses the genetic algorithm to optimize the expansion factor to achieve the purpose of the variable universe. The simulation results show that the variable universe fuzzy control method has good adaptability, robustness and anti-interference ability, and the control precision is very high, and it can solve the control difficulty caused by the coupling effect of each link, and has high application value for the uncertain robot system.