A 2-D Mode-Switching Quad-Core Oscillator Using E-M Mixed-Coupling Resonance Boosting

2020 ◽  
pp. 1-1
Author(s):  
Yiyang Shu ◽  
Huizhen Jenny Qian ◽  
Xun Luo
Keyword(s):  
Mode Switching

scholarly journals Research on predictive sliding mode control strategy for horizontal vibration of ultra-high-speed elevator car system based on adaptive fuzzy

2021 ◽  
Vol 54 (3-4) ◽  
pp. 360-373
Author(s):  
Hong Wang ◽  
Mingqin Zhang ◽  
Ruijun Zhang ◽  
Lixin Liu
Keyword(s):  
Sliding Mode Control ◽  
High Speed ◽  
Sliding Mode ◽  
Mode Switching ◽  
Parameter Uncertainties ◽  
Horizontal Vibration ◽  
Adaptive Fuzzy ◽  
Mode Control ◽  
System A ◽  
Ultra High Speed

In order to effectively suppress horizontal vibration of the ultra-high-speed elevator car system. Firstly, considering the nonlinearity of guide shoe, parameter uncertainties, and uncertain external disturbances of the elevator car system, a more practical active control model for horizontal vibration of the 4-DOF ultra-high-speed elevator car system is constructed and the rationality of the established model is verified by real elevator experiment. Secondly, a predictive sliding mode controller based on adaptive fuzzy (PSMC-AF) is proposed to reduce the horizontal vibration of the car system, the predictive sliding mode control law is achieved by optimizing the predictive sliding mode performance index. Simultaneously, in order to decrease the influence of uncertainty of the car system, a fuzzy logic system (FLS) is designed to approximate the compound uncertain disturbance term (CUDT) on-line. Furthermore, the continuous smooth hyperbolic tangent function (HTF) is introduced into the sliding mode switching term to compensate the fuzzy approximation error. The adaptive laws are designed to estimate the error gain and slope parameter, so as to increase the robustness of the system. Finally, numerical simulations are conducted on some representative guide rail excitations and the results are compared to the existing solution and passive system. The analysis has confirmed the effectiveness and robustness of the proposed control method.

scholarly journals A Bus-Sectionalized Hybrid AC/DC Microgrid: Concept, Control Paradigm, and Implementation

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3508
Author(s):  
Jing Li ◽  
Hongda Cai ◽  
Pengcheng Yang ◽  
Wei Wei
Keyword(s):  
Hierarchical Control ◽  
Mode Switching ◽  
Stable Operation ◽  
Service Reliability ◽  
Test Results ◽  
Dc Microgrid ◽  
Dc Microgrids ◽  
Operation Modes ◽  
Control Paradigm ◽  
Operational Data

In the last several years, the coordination control of hybrid AC/DC microgrids (HMGs) has been gaining increasingly more attention. However, most of these discussions are focused on single-bus HMGs whose AC or DC bus is not sectionalized by AC or DC breakers. Compared with these single-bus HMGs, the bus-sectionalized HMG has more flexible topologies, more diverse operation modes, and consequently higher service reliability. However, meanwhile, these benefits also bring challenges to the stable operation of bus-sectionalized HMGs, particularly for mode switching. Relying on the national HMG demonstrative project in Shaoxing, China, this paper makes efforts to present the hierarchical control paradigm of a typical bus-sectionalized HMG toward standardization. The test results demonstrate that the proposed system provides seamless switching and uninterrupted power supply without controller reconfiguration among different operation modes. The operational data are also brought forth and analyzed to provide significant and useful experiences for designing and developing similar HMGs in the future.

scholarly journals Hemodialysis exacerbates proteolytic imbalance and pro-fibrotic platelet dysfunction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Aaron J. Velasquez-Mao ◽  
Mark A. Velasquez ◽  
Zhengxiong Hui ◽  
Denise Armas-Ayon ◽  
Jingshen Wang ◽  
...  
Keyword(s):  
Blood Flow Rate ◽  
Mode Switching ◽  
Platelet Dysfunction ◽  
Compensatory Mechanisms ◽  
Before And After ◽  
Basal Plasma ◽  
Stage Renal Disease ◽  
End Stage ◽  
Plasma Factors ◽  
Esrd Patients

AbstractMulti-organ fibrosis among end stage renal disease (ESRD) patients cannot be explained by uremia alone. Despite mitigation of thrombosis during hemodialysis (HD), subsequent platelet dysfunction and tissue dysregulation are less understood. We comprehensively profiled plasma and platelets from ESRD patients before and after HD to examine HD-modulation of platelets beyond thrombotic activation. Basal plasma levels of proteolytic regulators and fibrotic factors were elevated in ESRD patients compared to healthy controls, with isoform-specific changes during HD. Platelet lysate (PL) RNA transcripts for growth and coagulative factors were elevated post-HD, with upregulation correlated to HD vintage. Platelet secretome correlations to plasma factors reveal acutely induced pro-fibrotic platelet phenotypes in ESRD patients during HD characterized by preferentially enhanced proteolytic enzyme translation and secretion, platelet contribution to inflammatory response, and increasing platelet dysfunction with blood flow rate (BFR) and Vintage. Compensatory mechanisms of increased platelet growth factor synthesis with acute plasma matrix metalloproteinase (MMP) and tissue inhibitor of MMPs (TIMP) increases show short-term mode-switching between dialysis sessions leading to long-term pro-fibrotic bias. Chronic pro-fibrotic adaptation of platelet synthesis were observed through changes in differential secretory kinetics of heterogenous granule subtypes. We conclude that chronic and acute platelet responses to HD contribute to a pro-fibrotic milieu in ESRD.

Refined Optimization Analysis of 2G/3G Mode Switching

2013 ◽  
Vol 443 ◽  
pp. 349-353
Author(s):  
Yu Zhang ◽  
Chun Yang Wang
Keyword(s):  
Basic Principle ◽  
Implementation Process ◽  
Typical Case ◽  
Mode Switching ◽  
Continuous Development ◽  
Optimization Analysis ◽  
Refined Method ◽  
High Efficient ◽  
Specific Implementation

With the continuous development of the 3rd generation telecommunication, the requirement of fluent switching is taken more consideration. The paper presents the relevant parameters and the implication of 2G/3G mode switching in CS domain. Proposes the optimization analysis of the basic principle of 2G/3G mode switching in CS domain, suggests a method using neighboring CIO to refine the origin switching methods, with the analysis of typical case by using the specific implementation process of neighboring CIO, the refined method proved to be of actual value and high efficient

scholarly journals Intuitive real-time control strategy for high-density myoelectric hand prosthesis using deep and transfer learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Simon Tam ◽  
Mounir Boukadoum ◽  
Alexandre Campeau-Lecours ◽  
Benoit Gosselin
Keyword(s):  
Real Time ◽  
Transfer Learning ◽  
Control Strategy ◽  
High Density ◽  
Fine Tuning ◽  
Mode Switching ◽  
Correct Prediction ◽  
Learning Approach ◽  
Predictive Values ◽  
Hand Prosthesis

AbstractMyoelectric hand prostheses offer a way for upper-limb amputees to recover gesture and prehensile abilities to ease rehabilitation and daily life activities. However, studies with prosthesis users found that a lack of intuitiveness and ease-of-use in the human-machine control interface are among the main driving factors in the low user acceptance of these devices. This paper proposes a highly intuitive, responsive and reliable real-time myoelectric hand prosthesis control strategy with an emphasis on the demonstration and report of real-time evaluation metrics. The presented solution leverages surface high-density electromyography (HD-EMG) and a convolutional neural network (CNN) to adapt itself to each unique user and his/her specific voluntary muscle contraction patterns. Furthermore, a transfer learning approach is presented to drastically reduce the training time and allow for easy installation and calibration processes. The CNN-based gesture recognition system was evaluated in real-time with a group of 12 able-bodied users. A real-time test for 6 classes/grip modes resulted in mean and median positive predictive values (PPV) of 93.43% and 100%, respectively. Each gesture state is instantly accessible from any other state, with no mode switching required for increased responsiveness and natural seamless control. The system is able to output a correct prediction within less than 116 ms latency. 100% PPV has been attained in many trials and is realistically achievable consistently with user practice and/or employing a thresholded majority vote inference. Using transfer learning, these results are achievable after a sensor installation, data recording and network training/fine-tuning routine taking less than 10 min to complete, a reduction of 89.4% in the setup time of the traditional, non-transfer learning approach.

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