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RISS 인기검색어
- 검색키워드
- 저자 : Zhihui Du (검색결과 4 건)
- 무료
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Quantized Consensus Control for Multi-UAVs based on Prescribed Performance
Zhihui Du,Jingping Shi,Zhonghua Wu 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.1
A distributed adaptive control approach based on a prescribed performance is proposed for multiple unmanned aerial vehicles (multi-UAVs) with disturbances and input quantization. The tracking error is converted into the consensus error by relying on the communication topology so that the distributed controller can be implemented. The radial basic function (RBF) neural network with composite learning is used to estimate the unknown nonlinear functions, and adaptive compensation terms are applied to compensate for the errors caused by filters and disturbances. A hysteretic quantizer is introduced to process the control input signal to relax the channel burden, and an estimator is implemented to solve the problem where the quantizer parameters are unknown. An improved Barrier Lyapunov function (BLF) is developed to ensure that the consensus error satisfies the prescribed performance requirements. Stability analysis proves that the tracking error and all signals in the closed-loop systems are bounded. Finally, all follower UAVs can track the virtual leader and maintain the given formation. A numerical simulation is provided to validate the effectiveness of the proposed control approach.
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Study on Waterborne Polyurethanes Based on Poly(dimethyl siloxane) and Perfluorinated Polyether
Yang Du,Chao Zhou,Zhihui Yang 한국고분자학회 2015 Macromolecular Research Vol.23 No.9
Methylsiloxane and fluorinated segments were introduced into the polymer backbone of polyurethane by direct reaction of isocyanate with dialcohol terminated perfluoropolyether (E10-H) and poly(dimethyl siloxane) (PDMS). The polyurethane structure was revealed by Fourier transform infrared spectrometer in ATR mode and Xray photoelectron spectroscope. It was found that the silicon and fluorine moieties easily migrated to the surface of material in film-forming process due to their lower energy, so the water contact angle on membrane surface was greatly enhanced (maximum 100.1º), and the hydrophobic property of material was improved. Different degree of phase separation was observed by scanning electron microscope. Increment of PDMS or E10-H content caused the phase separation obviously, but section of PDMS and E10-H modified polyurethane showed that phase separation reduced. The linear dynamic viscoelastic measurements indicated that the dynamic storage modulus of all samples increased with the increment of frequency, and PDMS modified WPU’s grew fastest. The slope of G' vs. G'' showed a decrement, so each sample had a shear thinning behavior. The perfluoropolyether oil was to reduce viscosity of the system.
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Design and Synthesis of Acid-resistant Zeolite T/NaY Composite Membrane for Water/Ethanol Separation
Xiangbo Li,Zhihui Zhou,Liang Chen,Chunlong Kong,Hongbin Du 대한화학회 2019 Bulletin of the Korean Chemical Society Vol.40 No.6
The random distribution of zeolite T on the porous α-Al2O3 tube during growth greatly limits its application in the industry. In this study, the defective zeolite T layer is modified with zeolite NaY. A continuous and dense zeolite T/NaY composite membrane is obtained through characterization by scanning electron microscope and X-ray diffraction. The resulting composite membrane exhibits high selectivity and high permeation flux for 90?wt % ethanol/water solution at 75 °C. Water concentration in the permeation side of the as-synthesized zeolite T/NaY composite membrane is >99.9 wt %, whereas that of primary zeolite T layer is only 60.4 wt %. The water permeation flux of the composite membrane reaches 4.35?kg/m2/h1. The composite membrane displays good stability in acid solution when the pH of the solution is >5.
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Research on the Prediction of Solar Energy Generation based on Measured Environmental Data
Guojing Zhang,Xiaoying Wang,Zhihui Du 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.5
As a kind of renewable energy, solar power becomes more and more widely used as the power supply for large-scale datacenters to save the brown energy consumption and to reduce the overall cost. The prediction accuracy of solar energy generation becomes a fundamental issue in the research of how to efficiently manage the renewable energy resources. This paper explores the possible ways to predict the solar radiation intensity based on the assumption that it impacts the solar power generation proportionally. Through the analysis and research of photovoltaic power generation system, we explore the influence factors for solar radiation intensity, establish a relationship of solar radiation intensity and ambient temperature, time, humidity, wind speed in the forecasting model, and finally established the multivariate linear regression model and artificial neural network model. According to the two models, the environmental monitoring data measured at the Qinghai University are employed as the basis of the prediction of solar radiation intensity, and compared with the actual measurement data monitoring system. Experimental results show that, by using the BP neural network prediction model, the achieved accuracy is higher than other empirical model. The prediction method and good results provide a necessary foundation for future related research based on solar radiation values forecasts.
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