Virtual Signal Injected MTPA Control for DTC Five-Phase IPMSM Drives

Liu, Guohai,Yang, Yuqi,Chen, Qian The Korean Institute of Power Electronics 2019 JOURNAL OF POWER ELECTRONICS Vol.19 No.4

This paper introduces a virtual signal injected maximum torque per ampere (MTPA) control strategy for direct-torque-controlled five-phase interior permanent magnet synchronous motor (IPMSM) drives. The key of the proposed method is that a high frequency signal is injected virtually into the stator flux linkage. Then the responding stator current is calculated and regulated to compensate the amplitude of the flux linkage. This is done according to the relationship between the stator current and the stator flux linkage. Since the proposed method does not inject any real signals into the motor, it does not cause any of the problems associated with high-frequency signals, such as additional copper loss and extra torque ripple. Simulation and experimental results are offered to verify the effectiveness of the proposed method.

Virtual Signal Injected MTPA Control for DTC Five-Phase IPMSM Drives

Guohai Liu,Yuqi Yang,Qian Chen 전력전자학회 2019 JOURNAL OF POWER ELECTRONICS Vol.19 No.4

This paper introduces a virtual signal injected maximum torque per ampere (MTPA) control strategy for direct-torquecontrolledfive-phase interior permanent magnet synchronous motor (IPMSM) drives. The key of the proposed method is that ahigh frequency signal is injected virtually into the stator flux linkage. Then the responding stator current is calculated andregulated to compensate the amplitude of the flux linkage. This is done according to the relationship between the stator currentand the stator flux linkage. Since the proposed method does not inject any real signals into the motor, it does not cause any of theproblems associated with high-frequency signals, such as additional copper loss and extra torque ripple. Simulation andexperimental results are offered to verify the effectiveness of the proposed method.

Higher-Order Conditional Random Field established with CNNs for Video Object Segmentation

( Chuanyan Hao ),( Yuqi Wang ),( Bo Jiang ),( Sijiang Liu ),( Zhi-xin Yang ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.9

We perform the task of video object segmentation by incorporating a conditional random field (CRF) and convolutional neural networks (CNNs). Most methods employ a CRF to refine a coarse output from fully convolutional networks. Others treat the inference process of the CRF as a recurrent neural network and then combine CNNs and the CRF into an end-to-end model for video object segmentation. In contrast to these methods, we propose a novel higher-order CRF model to solve the problem of video object segmentation. Specifically, we use CNNs to establish a higher-order dependence among pixels, and this dependence can provide critical global information for a segmentation model to enhance the global consistency of segmentation. In general, the optimization of the higher-order energy is extremely difficult. To make the problem tractable, we decompose the higher-order energy into two parts by utilizing auxiliary variables and then solve it by using an iterative process. We conduct quantitative and qualitative analyses on multiple datasets, and the proposed method achieves competitive results.

Progress in Preparation of Cellulase from Lignocellulose Using Fungi

Hui Jiao,Xiang-Yang Song,Chenhuan Lai,Hao Fang,Yuqi Song,Junjun Zhu 한국생물공학회 2021 Biotechnology and Bioprocess Engineering Vol.26 No.6

Lignocellulosic biomass such as agricultural and forestry waste is the most abundant renewable organic carbon source on earth and can be used to produce source of clean energy such as ethanol. One of the disadvantages of the preparation of ethanol using lignocellulose as raw material is the high cost of production of cellulase. Fungi are capable of effectively degrading lignocellulose and secreting a large amount of cellulase, and have the advantages of ease of preparation, high yield, and full enzyme systems. Therefore, this paper reviews sources of lignocellulose and the biodegradation properties which limit the production of cellulase, proposes micro-organisms capable of degrading lignocellulose and explains the types of cellulase, and the mechanism of action, methods of fermentation optimization, and control are analyzed, and ways to increase the yield of cellulase are described. Finally, research on the effects of inducers on the production of cellulase by fungi is reviewed. The aims of this review are to provide a reference for the efficient production and industrial application of cellulase.

Distributed Adaptive Neural Consensus Control for Stochastic Nonlinear Multiagent Systems with Whole State Delays and Multiple Constraints

Yukun Tao,Feifei Yang,Ping He,Congshan Li,Yuqi Ji 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.9

This paper presents a distributed adaptive neural tracking consensus control strategy for a class of stochastic nonlinear multiagent systems with whole state time delays, input and output constrains. The considered systems are involved in the existence of whole state delays and stochastic disturbances, which makes the controller design more difficult and complex. Firstly, time delays are related to unknown dynamic interactions with the whole states of the agent systems, and novel Lyapunov-Krasovskii functionals are constructed. Secondly, the smooth asymmetric saturation nonlinearity is given based on Gaussian error function, output constraints are achieved via barrier Lyapunov functions, and neural networks are utilized to deal with the completely unknown nonlinearities and stochastic disturbances. Then, based on Lyapunov stability theory, a delay-independent adaptive controller is developed via Lyapunov-Krasovskii functionals and backstepping technique, and it reduces the complexity of learning parameters. It is proved that the proposed approximation-based controller can guarantee that all closed-loop signals are cooperatively semi-globally uniformly ultimately bounded (CSGUUB), and the tracking errors between the followers and the leaders eventually converge to a small neighbourhood around the origin. Finally, simulation studies are carried out, and the simulation results verify the correctness and effectiveness of the proposed Strategy.

Trophoblast Cell Subtypes and Dysfunction in the Placenta of Individuals with Preeclampsia Revealed by Single‑Cell RNA Sequencing

Wenbo Zhou,Huiyan Wang,Yuqi Yang,Fang Guo,Bin Yu,Zhaoliang Su 한국분자세포생물학회 2022 Molecules and cells Vol.45 No.5

Trophoblasts, important functional cells in the placenta, play a critical role in maintaining placental function. The heterogeneity of trophoblasts has been reported, but little is known about the trophoblast subtypes and distinctive functions during preeclampsia (PE). In this study, we aimed to gain insight into the cell type-specific transcriptomic changes by performing unbiased single-cell RNA sequencing (scRNA-seq) of placental tissue samples, including those of patients diagnosed with PE and matched healthy controls. A total of 29,006 cells were identified in 11 cell types, including trophoblasts and immune cells, and the functions of the trophoblast subtypes in the PE group and the control group were also analyzed. As an important trophoblast subtype, extravillous trophoblasts (EVTs) were further divided into 4 subgroups, and their functions were preliminarily analyzed. We found that some biological processes related to pregnancy, hormone secretion and immunity changed in the PE group. We also identified and analyzed the regulatory network of transcription factors (TFs) identified in the EVTs, among which 3 modules were decreased in the PE group. Then, through in vitro cell experiments, we found that in one of the modules, CEBPB and GTF2B may be involved in EVT dysfunction in PE. In conclusion, our study showed the different transcriptional profiles and regulatory modules in trophoblasts between placentas in the control and PE groups at the single-cell level; these changes may be involved in the pathological process of PE, providing a new molecular theoretical basis for preeclamptic trophoblast dysfunction.