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Abstract
Servo systems affect the performances of machining in accuracy and surface quality for high speed and precision machine tools. This study introduces an efficient servo tuning technique for Computer Numerical Control (CNC) feed drive systems using particle swarm optimization (PSO) algorithm by virtual machine tool approach. The proposed approach contained a system identification phase and a servo tuning phase based on the same bandwidth for all axes feed drive systems. The PSO algorithm was adopted to obtain the system parameters and maximize the corresponding bandwidth. An efficient two-step servo tuning method based on gain and phase margins was proposed for high speed and precision requirements. All feed drive systems controller gains were optimized simultaneously for synchronization. A remote system called Machine Dr. was established for servo tuning and monitoring. Simulation and experimental results were introduced to illustrate the effectiveness of the proposed approach.
Highlights
Computer numerical control (CNC) machine tools have been widely used in high speed and precision machining, such as curved surface, gears, aerospace materials, integrated circuit (IC) parts, and precision components, etc
We introduce the particle swarm optimization (PSO) algorithm, an evolutionary computation technique proposed by Kennedy & Eberhart [23]
We focused on the bandwidth; it was adopted to obtain the estimation system are shown in Figure 7
Summary
Computer numerical control (CNC) machine tools have been widely used in high speed and precision machining, such as curved surface, gears, aerospace materials, integrated circuit (IC) parts, and precision components, etc. Some literature introduce virtual machine tools, including virtual CNC, servo models, and mechanical dynamics of feed drive systems, for treating the problem [11,12,13,14,15,16,17,18,19]. In order to employ the intelligent efficient method, this study developed a virtual CNC feed drive system via system identification technology using Heidenhain TNCopt software. This can obtain the characteristics of the system and the mathematical models which we can use in numerical.
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