Model predictive control of three-level active front-end converter with low switching frequency

In medium voltage-high power(MV-HP)applications,the high switching frequency of power converter will result in unnecessary energy losses,which directly affect efficiency.To resolve this issue,a novel finite control set-model predictive control(FCS-MPC)with low switching frequency for three-level neutral point clamped-active front-end converters(NPC-AFEs)is proposed.With this approach,the prediction model of three-level NPC-AFEs is established inα-βreference frame,and the control objective of low average switching frequency is introduced into a cost function.The proposed method not only achieves the desired control performance under low switching frequency,but also performs the efficient operation for the three-level NPC-AFEs.The simulation results are provided to verify the effectiveness of proposed control scheme.

Low-complexity model predictive control of a four-level active neutral point clamped inverter without weighting factors

The four-level active neutral point clamped(ANPC)inverter has become increasingly widely used in the renewable energy indus-try since it offers one more voltage level without increasing the total number of active switches compared to the three-level ANPC inverter.The model predictive current control(MPCC)is a promising control method for multi-level inverters.However,the conven-tional MPCC suffers from high computational complexity and tedious weighting factor tuning in multi-level inverter applications.A low-complexity MPCC without weighting factors for a four-level ANPC inverter is proposed in this paper.The computational burden and voltage vector candidate set are reduced according to the relationship between voltage vector and neutral point voltage balance.The proposed MPCC shows excellent steady-state and dynamics performances while ensuring the neutral point voltage balancing.The efficacy of the proposed MPCC is verified by simulation and experimental results.

Design of pharmacodynamic monitoring system based on acupuncture differential thermometry

To control drug effects by detecting temperature difference between biologically active point（BAP）and intact area of skin for treatment of mental illness,a device is developed for monitoring the temperature of BAP and the dose medication and its change in real time to increase effectiveness of treatment.Two electrodes by Foll R method are used and BAP is determined based on topographic anatomical reference points.The temperature values are measured by integral thermometers DS18B20.the received data are processed and temperature difference is calculated and displayed under the control of microcontroller Atmega32.The obtained data confirm the correlation between the temperature difference indicators BAP C7,Gi4 and neurological scales assessing severity of mental illness.The experimetal results show that the temperature difference can be criteria for evaluating the effects of drugs,which is the basis for computer control systems of of medical process of mental patients.

Surface Modification and Model of Glassy Cementitious Materials

Basic theory of surface modification about glassy cementitous materials is presented. At the same time modified glassy cementitous materials were manufactured by means of point activation and disperse and grind aid according to technology of mechanical-chemistry. This theory about surface modification has been proved by some experimental results such as SEM, size distribution, fluidity of the paste, physical-mechanical properties of the hardened paste and heat of the hydration. The particle size of modified fly ash is tending to become smaller and the shape of microfine particles seems a ball; strength of modified glassy cementitous materials and ordinary portland cement compound paste has a obvious increment and fluidity of the paste also has a noticeable improvement; surface modification also can accelerate the formation of paste structure to a certain degree. Besides a model about the interactive mechanism of modified glassy cementitous materials and ordinary portland cement is put forward.

Biotechnical system based on fuzzy logic prediction for surgical risk classification using analysis of current-voltage characteristics of acupuncture points

Objective:This study aimed to develop expert fuzzy logic model to assist physicians in the prediction of postoperative complications of prostatic hyperplasia before surgery.Methods:A method for classification of surgical risks was developed.The effect of rotation of the current–voltage characteristics at biologically active points(acupuncture points)was used for the formation of classifier descriptors.The effect determined reversible and non-reversible changes in electrical resistance at acupuncture points with periodic exposure to a sawtooth probe current.Then,the developed method was tested on the prediction of the success of surgical treatment of benign prostatic hyperplasia.Results:Input descriptors were obtained from collected data including current-voltage characteristics of 5 acupuncture points and composed of 27 arrays feeding in the model.The maximum diagnostic sensitivity of the classifier for the success of a surgical operation in the control sample was 88%and for testing data set prediction accuracy was 97%.Conclusion:The use of tuples of current-voltage characteristic descriptors of acupuncture points in the classifiers could be used to predict the success of surgical treatment with satisfactory accuracy.The model can be a valuable tool to support physicians’diagnosis.

Organic carboxylate-assisted engineering for fabricating Fe,N co-doped porous carbon interlinked carbon nanotubes towards boosting the oxygen reduction reaction for Zn-air batteries

Fe-N_x sites have been identified as core descriptors for Fe-N/C based oxygen reduction reaction catalysts.However, the low density and less utilization of Fe-Nxsites render these catalysts with inefficient catalytic performance. Herein, we develop an organic carboxylate-assisted engineering to construct Fe, N co-doped porous carbon interlinked carbon nanotubes(Fe/N-CCNTs) with high-density and sufficiently exposed FeNxsites based on self-catalyzed effect. The existing forms of Fe include Fe-imidazole configuration and coordination with unsaturated Zn sites via organic carboxylate as linkers, leading to high-density Fe-N_x sites after pyrolysis. Besides, hexatomic carbon rings of organic carboxylate lower cyclization energy barrier for CNT formation, resulting in CNTs interlinked with separated active sites through “active pointconductive line-active point” connections. The optimal sample(Fe-BOAc-PNC) exhibits the onset potential of 0.93 V(vs. RHE) and half-wave potential of 0.84 V in alkaline solution. The liquid-state Zn-air battery(ZAB) employing Fe-BOAc-PNC generates large power density(160 m W/cm^(2)) and stability over 160 h.Moreover, the assembled flexible ZAB displays superb power density of 93 m W/cm^(2) with robust flexibility. This work provides an insightful perspective for designing Fe-N/C catalysts with high-density and sufficiently exposed active sites for energy storage application.