Experimental Research on Effects of Process Parameters on Servo Scanning 3D Micro Electrical Discharge Machining

Servo scanning 3D micro electrical discharge machining (3D SSMEDM) is a novel and effective method in fabricating complex 3D micro structures with high aspect ratio on conducting materials. In 3D SSMEDM process, the axial wear of tool electrode can be compensated automatically by servo-keeping discharge gap, instead of the traditional methods that depend on experiential models or intermittent compensation. However, the effects of process parameters on 3D SSMEDM have not been reported up until now. In this study, the emphasis is laid on the effects of pulse duration, peak current, machining polarity, track style, track overlap, and scanning velocity on the 3D SSMEDM performances of machining efficiency, processing status, and surface accuracy. A series of experiments were carried out by machining a micro-rectangle cavity (900 μm×600 μm) on doped silicon. The experimental results were obtained as follows. Peak current plays a main role in machining efficiency and surface accuracy. Pulse duration affects obviously the stability of discharge state. The material removal rate of cathode processing is about 3/5 of that of anode processing. Compared with direction-parallel path, contour-parallel path is better in counteracting the lateral wear of tool electrode end. Scanning velocity should be selected moderately to avoid electric arc and short. Track overlap should be slightly less than the radius of tool electrode. In addition, a typical 3D micro structure of eye shape was machined based on the optimized process parameters. These results are beneficial to improve machining stability, accuracy, and efficiency in 3D SSMEDM.

Robust tracking control for micro machine tools with load uncertainties

The quality of the micro-mechanical machining outcome depends significantly on the tracking performance of the miniaturized linear motor drive precision stage. The tracking behavior of a direct drive design is prone to uncertainties such as model parameter variations and disturbances. Robust optimal tracking controller design for this kind of precision stages with mass and damping ratio uncertainties was researched. The mass and damping ratio uncertainties were modeled as the structured parametric uncertainty model. An identification method for obtaining the parametric uncertainties was developed by using unbiased least square technique. The instantaneous frequency bandwidth of the external disturbance signals was analyzed by using short time Fourier transform technique. A two loop tracking control strategy that combines the p-synthesis and the disturbance observer （DOB） techniques was proposed. The p-synthesis technique was used to design robust optimal controllers based on structured uncertainty models. By complementing the/z controller, the DOB was applied to further improving the disturbance rejection performance. To evaluate the positioning performance of the proposed control strategy, the comparative experiments were conducted on a prototype micro milling machine among four control schemes： the proposed two-loop tracking control, the single loop μ control, the PID control and the PID with DOB control. The disturbance rejection performances, the root mean square （RMS） tracking errors and the performance robustness of different control schemes were studied. The results reveal that the proposed control scheme has the best positioning performance. It reduces the maximal errors caused by disturbance forces such as friction force by 60% and the RMS errors by 63.4% compared with the PID control. Compared to PID with DOB control, it reduces the RMS errors by 29.6%.

Active Disturbance Rejection Control for PMLM Servo System in CNC Machining

Uncertain friction is a key factor that influences the accuracy of servo system in CNC machine.In this paper,based on the principle of Active Disturbance Rejection Control(ADRC),a control method is proposed,where both the extended state observer(ESO) and the reduced order extended state observer(RESO) are used to estimate and compensate for the disturbance.The authors prove that both approaches ensure high accuracy in theory,and give the criterion for parameters selection.The authors also prove that ADRC with RESO performs better than that with ESO both in disturbance estimation and tracking error.The simulation results on CNC machine show the effectiveness and feasibility of our control approaches.