No abstract

The ripple normal force of permanent magnet linear synchronous motor (PMLSM) can directly deteriorate the machining accuracy of ultra-precision CNC machine tool which use linear motor direct drive. First, the normal force of PMLSM was calculated using finite element method (FEM) .then, id current compensate lookup table was established by indexing iq current, gap and position of mover .In order to reduce the ripple of normal force and keep the thrust steady, PMLSM current compensation control system was realized by injecting the id current to counteract the normal force ripples using field oriented control (FOC) method. The effectiveness of this proposed method is verified by the simulation using Matlab according to the comparison between the compensation and no compensation cases.

Air pollution may cause pernicious effects on human health, and is a widespread problem in the world. Air quality management systems have became an important research issue with strong implications for inhabitants’ health. Monitoring and forecasting of air quality indicators plays an important role in the management systems. Artificial intelligent techniques are successfully used in modelling of highly complex and nonlinear phenomena. In this paper, a model, which is radial basis function (RBF) neural network, is established to estimate the impact of meteorological indicators on SO2. The proposed model achieves 9.91% in mean absolute percentage error (MAPE) compared to real observation data sequence. For air quality, it could be a promising candidate for forecasting the air quality indicators data sequence.

For the characteristics of permanent magnet linear motor (PMLSM) servo system in machine tool feeding system suffering from the effect of parameter variations, load disturbances and so on, the time-varying sliding mode position and speed controller was designed. By designing the time-varying sliding mode line, the line is changing with time t and its slope does not change during the control process. And the error state of the control system always lies on the sliding mode line from the beginning of any initial state. The reaching phase is eliminated. During the design process, because of the control signal is restricted, optimize the controller parameters by minimizing the integral absolute error (IAE). And the convergence rate of error is speeded up. The simulation results prove that the system have global robustness to the parameter variations and disturbance.

In order to reduce the cogging torque in dual-rotor permanent magnet (PM) ring torque motor, the expression of cogging torque is deduced on the motor, and the influence rules of the resulting cogging torque are analyzed with change the inner and outer slot opening widths. According to the dual-rotor PM ring torque machine, the method for reducing the cogging torque amplitude and leading a reverse phase torque curve by suitable selection of the inner and outer slot opening widths is proposed. The results of simulation show that selecting the appropriate slot opening widths can effectively reduce cogging torque by the finite element simulation method.