Force and Torque Model of Magnetically Levitated System with 2D Halbach Array and Printed Circuit Board Coils.

Precision machining fields often require worktables with different stroke sizes. To address the need for scalability and facilitate manufacturing, this study proposes a novel infinite expansion magnetically levitated planar motor (MLPM) based on PCB stator coils. Different from existing magnetic levitation systems that use PCB coils, the design presented in this paper utilizes smaller coil units, with each coil being independent of one another. The coils are structured in a spiral pattern on a 16-layer PCB, comprising 15 layers of coils, while the last layer is dedicated to wiring and other circuits. Magnetic field modeling is conducted for both the stator coil and the 2D Halbach array structure employed in the system. A simple table lookup method is employed to accurately account for the prevalent end effects observed during system motion. Additionally, the decoupling effect of magnetic force and torque is evaluated by solving for the current vector at different points along a specific trajectory. To verify the accuracy of the proposed system's modeling, a prototype is developed and tested. Experimental results demonstrate that compared to traditional harmonic model methods, the proposed approach improves the calculation accuracy of magnetic force by 50.31% and torque by 70.65%. This study presents a new MLPM system with vast potential applications in precision manufacturing and robotics. The innovative design and improved performance characteristics make it a promising technology for enhancing the capabilities of worktables in precision machining fields.

Iterative neural network adaptive robust control of a maglev planar motor with uncertainty compensation ability.

In this paper, an iterative neural network adaptive robust control (INNARC) strategy is proposed for the maglev planar motor (MLPM) to achieve good tracking performance and uncertainty compensation. The INNARC scheme consists of adaptive robust control (ARC) term and iterative neural network (INN) compensator in a parallel structure. The ARC term founded on the system model realizes the parametric adaptation and promises the closed-loop stability. The INN compensator based on the radial basis function (RBF) neural network is employed to handle the uncertainties resulted from the unmodeled non-linear dynamics in the MLPM. Additionally, the iterative learning update laws are introduced to tune the network parameters and weights of the INN compensator simultaneously, so the approximation accuracy is improved along the system repetition. The stability of the INNARC method is proved via the Lyapunov theory, and the experiments are conducted on an home-made MLPM. The results consistently demonstrate that the INNARC strategy possesses the satisfactory tracking performance and uncertainty compensation, and the proposed INNARC is an effective and systematic intelligent control method for MLPM.

Development of Magnetically Levitated Rotary Table for Repetitive Trajectory Tracking.

The magnetic levitation system has been considered as a promising actuator in micromachining areas of study. In order to improve the tracking performance and disturbance rejection of the magnetically levitated rotary table, an iterative learning PID control strategy with disturbance compensation is proposed. The estimated disturbance compensates for the control signals to enhance the active disturbance rejection ability. The iterative learning control is used as a feed-forward unit to further reduce the trajectory tracking error. The convergence and stability of the iterative learning PID with disturbance compensation are analysed. A series of comparative experiments are carried out on the in-house, custom-made, magnetically levitated rotary table, and the experimental results highlight the superiority of the proposed control strategy. The iterative learning PID with disturbance compensation enables the magnetically levitated rotary table to realize good tracking performance with complex external disturbance. The proposed control strategy strengthens the applicability of magnetically levitated systems in the mechanism manufacturing area.

Deep Federated Adaptation: An Adaptative Residential Load Forecasting Approach with Federated Learning.

Residential-level short-term load forecasting (STLF) is significant for power system operation. Data-driven forecasting models, especially machine-learning-based models, are sensitive to the amount of data. However, privacy and security concerns raised by supervision departments and users limit the data for sharing. Meanwhile, the limited data from the newly built houses are not sufficient to support building a powerful model. Another problem is that the data from different houses are in a non-identical and independent distribution (non-IID), which makes the general model fail in predicting accurate load for the specific house. Even though we can build a model corresponding to each house, it costs a large computation time. We first propose a federated transfer learning approach applied in STLF, deep federated adaptation (DFA), to deal with the aforementioned problems. This approach adopts the federated learning architecture to train a global model without undermining privacy, and then the model leverage multiple kernel variant of maximum mean discrepancies (MK-MMD) to fine-tune the global model, which makes the model adapted to the specific house's prediction task. Experimental results on the real residential datasets show that DFA has the best forecasting performance compared with other baseline models and the federated architecture of DFA has a remarkable superiority in computation time. The framework of DFA is extended with alternative transfer learning methods and all of them achieve good performances on STLF.

The Laser Rangefinder System in Quadrature Modem and Ambiguity Resolution.

We propose a laser rangefinder system based on the quadrature modem to achieve amplitude modulation, the method improves the accuracy of the phase measuring and simplifies the hardware design compared to the system with the secondary mixing methods, and to solve the range ambiguity caused by the measuring process, the ranging ambiguity resolving algorithm based on the over-determined equation is proposed, which avoids the searching of the optimal solution, finally the two K60 laser rangefinders and three proposed rangefinders were experimented on the national standard baseline with the precision of 0.18 mm. the measuring time of the proposed system is less than 1.8 s, the average measuring error of those three prototypes is less than 2 mm, and the standard deviation is less than 1 mm within the measuring range 0~60 m. The experimental results show that the proposed design system of the rangefinder has higher measurement accuracy and speed in comparison with the traditional ones, which indicates the high reliability of the proposed design system.

Tumor boundary detection in ultrasound imagery using multi-scale generalized gradient vector flow.

PURPOSE: As a key technology in high-intensity focused ultrasound (HIFU) ablation systems, a precise ultrasound image segmentation method for tumor boundary detection is helpful for ablation of tumors and avoiding tumor recurrence. This study explores a new deformable snake model called multi-scale generalized gradient vector flow (MS-GGVF) to segment ultrasound images in HIFU ablation. METHODS: The main idea of the technique is dealing with two issues including spurious boundary attenuation and setting the standard deviation of the Gaussian filter. We assign the standard deviation as scales to build the MS-GGVF model and create a signed distance map to use its gradient direction information and magnitude information to refine the multi-scale edge map by attenuating spurious boundaries and highlighting the real boundary. In addition, a fast generalized gradient vector flow computation algorithm based on an augmented Lagrangian method is introduced to calculate the external force vector field to improve the computation efficiency of our model. RESULTS: The experimental segmentations were similar to the ground truths delineated by two medical physicians with high area overlap measure and low mean contour distance. CONCLUSION: The experimental results demonstrate that the proposed algorithm is robust, reliable, and precise for tumor boundary detection in HIFU ablation systems.

An improved balloon snake for HIFU image-guided system.

Target segmentation in ultrasound images is a key step in the definition of the intro-operative planning of high-intensity focused ultrasound therapy. This paper presents an improvement for the balloon snake in segmentation. A sign function, designed by the edge map and the moving snake, is added to give the direction of the balloon force on the moving snake separately. Segmentation results are demonstrated on ultrasound images and the effectiveness and convenience shown in applications.

[Motion control of moving mirror based on fixed-mirror adjustment in FTIR spectrometer].

The performance of the uniform motion of the moving mirror, which is the only constant motion part in FTIR spectrometer, and the performance of the alignment of the fixed mirror play a key role in FTIR spectrometer, and affect the interference effect and the quality of the spectrogram and may restrict the precision and resolution of the instrument directly. The present article focuses on the research on the uniform motion of the moving mirror and the alignment of the fixed mirror. In order to improve the FTIR spectrometer, the maglev support system was designed for the moving mirror and the phase detection technology was adopted to adjust the tilt angle between the moving mirror and the fixed mirror. This paper also introduces an improved fuzzy PID control algorithm to get the accurate speed of the moving mirror and realize the control strategy from both hardware design and algorithm. The results show that the development of the moving mirror motion control system gets sufficient accuracy and real-time, which can ensure the uniform motion of the moving mirror and the alignment of the fixed mirror.