In the field of optical engineering, the laser position control system has important role in many applications, such as measurement, communication, fabrication. Traditional methods to solve laser position control system often face the problems of insufficient generalization, such as configuration or singular solution. In this study we proposed a novel model- free reinforcement learning approach based Proximal Policy Optimization (PPO) for laser position control system. To control the position of laser, we develop an efficient representation of environmental inputs and outputs. Position error of Position Sensing Detector (PSD), and three kinds of distance parameters are applied our environmental parameters. To overcome the challenges associated with training in real worlds, we developed training environment in simulation. The simulation to evaluate performance of our approach, we perform several times of experiments in both simulated and real world system.
A magnetic levitation system (MLS) controls the position of a steel ball with the magnetic force of the electromagnetic actuator. A disturbance observer (DOB) could improve the disturbance rejection and command tracking performance of the voltage-controlled MLS. This paper studied control boost of MLS using current and position DOB. The current-controlled MLS had a higher control performance than the voltage-controlled MLS. The combination of PID position and PI current controls provided stable levitation and a wide operation range of MLS. When DOB was applied to PI current control, it could compensate for inductance change according to the position of the steel ball. In addition, when another DOB was introduced to the PID position control, it improved the disturbance removal performance. Finally, we discussed the effectiveness and limitations of the DOB-based current and position control by measuring closed-loop frequency responses.
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Improvement of the Transient Levitation Response of a Magnetic Levitation System Using Hybrid Fuzzy and Artificial Neural Network Control Yupeng Zheng, Hyeong-Joon Ahn International Journal of Precision Engineering and Manufacturing.2025; 26(5): 1159. CrossRef
Computer numerical control (CNC) part programs generated by computer-aided manufacturing software are frequently composed of numerous G01 blocks. CNC interpolator applies acceleration and deceleration to generate velocity profile of each block. Therefore, the machining time is increased when the number of G01 blocks is increased. To reduce the machining time, corner blending has been used to smooth the corner shape of adjacent blocks. Because the tool path generated by corner bending dose not reach the commanded endpoint, error of the interpolated tool path exists. The objective of this study was to present a method to determine block overlap time to limit tool path error generated by corner blending. An algorithm to calculate tool path error with respect to block overlap time was also proposed. Performance of the proposed algorithm to limit tool path error was demonstrated in this study.
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