| MECHANICAL ENGINEERING |
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Motor servo control parameter tuning for parallel and hybrid machine tools based on a genetic algorithm |
| WANG Liping, KONG Xiangyu, YU Guang |
| State Key Laboratory of Tribology, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China |
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Abstract The motor servo control of machine tools influences the processing efficiency and processing quality of the machine tool. Most servo motor controllers use the proportional integral derivative (PID) control which depends on accurate determination of the control parameters. However, accurate determination of the control parameters requires much time, effort and experience with manual tuning usually required to provide the desired accuracy. This paper presents a method for tuning servo control parameters based on a genetic algorithm. A theoretical model is developed and refined based on the machine tool conditions. The fitness function is developed based on the parallel and hybrid machine tool characteristics with alarm indexes and optimal indexes. The servo control parameters given by the genetic algorithm are then tested on a 5-axis hybrid machine tool. The results show that the optimized parameters give better servo motor following accuracy than the engineer's parameters.Thus, this parameter tuning method based on a genetic algorithm saves time and effort while giving more accurate servo control parameters.
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| Keywords
servo motor
proportional integral derivative (PID) parameter tuning
genetic algorithm
parallel machine tool
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Issue Date: 26 August 2021
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2021,
Vol. 61
