This work focuses on the thrust ripple reduction in permanent magnet synchronous linear motors (PMSLMs), which are applied to laser cutting machines. To meet the high precision performance requirements of laser cutting machines, a novel auxiliary suppression device, tuned viscoelastic damper (TVD), is designed to reduce thrust ripple of PMSLM. First, TVD is designed with the structure and motion characteristics of PMSLM. The PMSLM with TVD is an integrated structure. Then, the equivalent magnetization method is used to analyze the PMSLM thrust, which is the excitation of TVD. Under the excitation of the PMSLM thrust, the damping force of TVD is expressed by Kelvin model and validated by finite element analysis (FEA). Subsequently, the thrust of PMSLM with TVD is obtained by adding the PMSLM thrust and TVD damping force. Finally, the thrust ripple rate is selected as a performance index of TVD in reducing thrust ripple. Simulation is performed to confirm the theoretical analysis. A prototype of PMSLM with TVD is manufactured and experiments are conducted to validate the effectiveness of the proposed auxiliary suppression device.

The split ratio, defined as the outer radius ratio of the magnet to stator, has been investigated and optimized in surface-mounted permanent magnet (PM) machines having conventional/novel pieced Halbach magnet array. The air-gap magnetic field in PM machine with novel pieced Halbach magnet has been analytically obtained. The influences of split ratio and magnet arc length ratio on the torque density have been separately and analytically investigated for the machines with conventional pieced Halbach magnet array. In order to achieve the maximal torque density in the conventional pieced Halbach magnetized machines, the optimum split ratio and/or pole arc ratio have been obtained. In addition, the influences of one or both of the split ratio and magnetization angle on the torque density have been analytically investigated for the machines with novel pieced Halbach magnet array. In order to achieve the maximal torque density in the novel pieced Halbach magnetized machines, the optimum split ratio and/or magnetization angle have been determined. Finally, the linear analytical predictions have been compared with linear and nonlinear finite element analyses.

This paper proposes a hierarchical optimization method for the energy scheduling of multiple microgrids (MMGs) in the distribution network of power grids. An energy market operator (EMO) is constructed to regulate energy storage systems (ESSs) and load demands in MMGs. The optimization process is divided into two stages. In the first stage, each MG optimizes the scheduling of its own ESS within a rolling horizon control framework based on a long-term forecast of the local photovoltaic (PV) output, the local load demand and the price sent by the EMO. In the second stage, the EMO establishes an internal price incentive mechanism to maximize its own profits based on the load demand of each MG. The optimization problems in these two stages are solved using mixed integer programming (MIP) and Stackelberg game theory, respectively. Simulation results verified the effectiveness of the proposed method in terms of the promotion of energy trading and improvement of economic benefits of MMGs.

This paper proposes a new high-precision rotor position measurement (RPM) method for permanent magnet spherical motors (PMSMs). In the proposed method, a LED light spot generation module (LSGM) was installed at the top of the rotor shaft. In the LSGM, three LEDs were arranged in a straight line with different distances between them, which were formed as three optical feature points (OFPs). The images of the three OFPs acquired by a high-speed camera were used to calculate the rotor position of PMSMs in the world coordinate frame. An experimental platform was built to verify the effectiveness of the proposed RPM method.

The output torque is an important performance indicator of a motor. Due to the special structure of a permanent magnet spherical motor (PMSM), it is difficult to measure its torque. This paper proposes a novel method to measure the output torque of the PMSM. The proposed method uses the microelectromechanical system (MEMS) gyroscope to measure the rotor motion acceleration, which is then used to calculate the output torque based on the rotor dynamics equation. In this paper, we firstly simulate and analyze the output torque of the PMSM. Secondly, we design a torque-measuring device to measure the output torque. Thirdly, we compare and discuss the experimental and simulation results. The comparison results show that the proposed method is feasible.

This paper presents an approach for input-to- state stabilization of dynamic neural networks, which extends the existing result in the literature to a wider class of systems. With the help of Sontag's formula, we create a scalar function to develop a new methodology for input-to-state stabilization of a class of dynamic neural network systems without a restriction on the number of inputs. In addition, the proposed design achieves global asymptotic stability and global inverse optimality with respect to a meaningful cost functional. A numerical example demonstrates the performance of the approach.