Cooperative Control for Dual Permanent Magnet Motor System with Unified Nonlinear Predictive Control

In order to improve the position tracking precision of dual permanent magnet synchronous motor (PMSM) systems, a unified nonlinear predictive control (UNPC) strategy based on the unified modeling of two PMSM systems is proposed in this paper. Firstly, establishing a unified nonlinear model of the dual-PMSM system, which contains uncertain disturbances caused by parameters mismatch and external load changes. Then, the position contour error and tracking errors are regarded as the performance index inserted into the cost function, and the single-loop controller is obtained by optimizing the cost function. Meanwhile, the nonlinear disturbance observer is designed to estimate the uncertain disturbances, which is used for feed-forward compensation control. Finally, the proposed strategy is experimentally validated on two 2.3 kW permanent magnet synchronous motors, and the experimental results show that effectiveness and feasibility of proposed strategy.

Flow Field Simulation And Experimental Investigation On Macro Electrolyte Jet Electrochemical Turning of TB6 Titanium Alloy

Electrolyte jet electrochemical turning is an effective method to realize high-quality machining of titanium alloy rotating components; however, minimal research has been carried out in this field. This is because it is difficult to control the machining flow field, which leads to poor machining surface quality. In this work, numerical simulations were used to optimize the machining flow field and reduce the proportion of gas that mixed into the machining area. This can promote participation of the tool electrode tip in the electrochemical reaction and improve the machining efficiency. The effectiveness of the optimized machining flow field for jet electrochemical turning was verified experimentally. The results showed that all three kinds of revolving TB6 titanium alloy samples with different structures could maintain the original contour shape, with a contour error <1% and a machined surface roughness reaching Ra 2.414 μm. The results demonstrate the application potential of the jet electrochemical turning process.

Kinematic Analysis and Parameter Measurement for Multi-Axis Laser Engraving Machine Tools

Multi-axis Laser Engraving Machine Tools (LEMT) are widely used in precision processing of parts with complex surface. The accuracy of kinematic model and parameter measurement are the key factors determining the processing quality of LEMT. In this paper, a kinematic model of multi-axis LEMT was established based on Homogeneous Transformation Matrix (HTM). Two types of unknown parameters, linkage parameters and positioning parameters, were measured in the presented model. Taking advantage of the characteristics of laser processing, this paper proposed a rapid measurement method of linkage parameters by combining the machine tool motion with the laser marking action. For positioning parameters, this study proposed a non-contact measurement method based on structured light scanner, which can obtain the translation values and the rotation values from the Workpiece Coordinate System (WCS) to the Basic Coordinate System (BCS) simultaneously. After the measurement of two kinds of parameters of a multi-axis LEMT was completed, the processing of a spatial curve was performed and the average contour error was controlled at 15.1 µm, which is sufficient to meet the project requirements.

Mapping Relation between Contour Error Components of Crankshaft Pin Journal and Axis Position Control Error of Oscillating Grinding Machine

Automatic crankshaft production lines require high reliability and accuracy stability for the oscillating grinding machine. Crankshaft contour error represent the most intuitive data in production field selective inspection. If the mapping relation between the contour error components of the crankshaft pin journal and the axis position control error of the oscillating grinding machine can be found, it would be great significance for the reliability maintenance of the oscillating grinding machine. Firstly, a contour error decomposition method based on ensemble empirical mode decomposition (EEMD) is proposed. Secondly, according to the contour generating principle of the pin journal by oscillating grinding, a calculation method to obtain the effect of the axis position control error of the oscillating grinder on the contour error of the pin journal is proposed. Finally, through the grinding experiments, the error data are acquired and measured to calculate and decompose the contour error by using the proposed methods for obtaining the mapping relation between the crankshaft pin journal contour error and the axis position control error. The conclusions show that the proposed calculation and decomposition methods can obtain the mapping relation between the contour error components of the crankshaft pin journal and the axis position control error of the oscillating grinding machine, which can be used to predict the key functional component performance of the machine tool from the oscillating grinding workpiece contour error.

Surface contour error model of five-axis machining considering multifactor coupling effects

During five-axis flank milling procedure, the static deflection of workpiece and cutter creates surface errors that lead to defects in projects with strict requirements, especially in thin-walled parts industry. Focusing on the mentioned issues, the surface contour error is predicted in this paper considering the coupling between the deflection and cutting force. First, an efficient calculation method of the cutting force is presented in five-axis flank milling. This method accounts for the impact of cutter runout on cutter/workpiece engagement (CWE) and the instantaneous undeformed chip thickness (IUCT). Then, a cutter is modelled as a cantilever structure and thus an analytical solution for the deflection of the end mill can be obtained. Next, the flexible cutting force is distributed on a finite element (FE) model of workpiece, while the workpiece stiffness keeps varying with the material removal. Subsequently, a flexible iterative calculation method for achieving deflection prediction is established. Finally, the prediction model is proven by machining tests of an S-shaped specimen in which predicted values of the surface error match with the experimental results.