| Summary: | 碩士 === 國立中興大學 === 機械工程學系所 === 106 === As the industry is trend to automatic and intelligent and the precision requirements of finished products in the manufacturing industry are getting higher and higher. Consequently, the academic research of virtual machine tools is increasing. The purpose of this thesis is to develop a virtual model of the feed drive system of the five-axis machine tool and propose an intelligent servo tuning method under the virtual environment. Finally, we apply the tuning results to the five-axis machine tool (MCU-5X) at National Chung Hsing University, Taiwan.
At first, we create a virtual model with physical parameters and consider the influences of friction and backlash. In order to establish the virtual system and predict the response of the actual machine tool, we use the particle swarm optimization (PSO) algorithm to propose the system identification methods for the feed drive system, friction, and backlash, respectively. The comparisons between the experiment and the simulation are introduced to illustrate the validation of our results and the results show that the proposed identification methods and the virtual system are reliable. On the other hand, we also propose a three-stage intelligent servo tuning method which adjusts the controller parameters of the speed loop, position loop, and feedforward loop, respectively. Finally, this thesis establishes the virtual servo control feed drive system and intelligent tuning machine, and applies the controller parameters after the servo tuning to the five-axis machine tool (MCU-5X) for circular test. The experimental results show that the rounding performance of the machine tool is improved.
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