Double-layer fuzzy adaptive NMPC coordinated control method of energy management and trajectory tracking for hybrid electric fixed wing UAVs

The energy management and trajectory tracking control are crucial to realize long-endurance autonomous flight for hybrid electric UAVs. This study aims to comprehensively consider energy management and trajectory tracking for hybrid electric fixed wing UAVs with photovoltaic panel/fuel cell/battery. A double-layer fuzzy adaptive nonlinear model predictive control method (DFNMPC) is proposed. Separated by the surplus demand power, energy management and trajectory tracking problem are decoupled into the high-layer fuzzy adaptive nonlinear model predictive controll problem (H-FNMPC) and low-layer fuzzy adaptive nonlinear model predictive controll problem (L-FNMPC). H-FNMPC solves the trajectory tracking and navigation control probelm for the greatest benefit of solar energy. L-FNMPC solves the power allocation problem of hybrid energy system for minimum equivalent hydrogen consumption. A fuzzy adaptive prediction horizon adjustment method based on UAV maneuvering degree is proposed to effectively improve proposed method adaptability to different mission profiles. Analogously, a fuzzy adaptive equivalent hydrogen consumption factor adjustment method in L-FNMPC is proposed to ensure the flexible utilization of battery. In addition, an equivalent hydrogen flow rate calculation method based on the real-time current ratio is proposed for PV/FC/Battery hybrid energy system. Numerical simulation results including a spiral trajectory tracking and a quadrilateral trajectory tracking, demonstrate that DFNMPC can simultaneously handle energy management and trajectory tracking problem for hybrid electric UAVs. Compared to hierarchical fuzzy state machine strategy, DFNMPC can save 13.3% hydrogen for the spiral trajectory tracking, and 56.9% for the quadrilateral trajectory tracking. It indicates that the energy efficiency can be improved from both levels of energy management and flight motion. The proposed method prospected for exploring high-energy-efficiency autonomous flight of hybrid electric UAVs in the future.     

Enhanced electrical and photoluminescence properties of BiSbO4-doped CaCu3Ti4O12 ceramics by modifying grain boundary response

CaCu₃Ti₄O₁₂-xwt%BiSbO₄ ceramics (CCTO-xwt%BSO, x = 0, 1, 2, 3) were prepared by solid-state reaction method. The microstructure, dielectric properties, varistor properties, photoluminescence properties of CCTO-xwt%BSO ceramics were studied in this work. Results showed that all samples formed CaCu₃Ti₄O₁₂ (CCTO) single phase. Doping BiSbO₄ (BSO) restrained the abnormal grain growth and increased the grain boundary density of ceramics. The introduction of BSO led to the increase of the grain boundary resistance, reducing the dielectric loss and enhancing the temperature stability of dielectric properties. The nonlinear electrical characteristics are enhanced with proper concentration of BSO. And the improved varistor performance with breakdown electric field of ～3.98–34.6 and nonlinear coefficient of ～1.49–2.96 are obtained for CCTO-xwt%BSO samples. In addition, the photoluminescent emission of the samples is enhanced with the addition of appropriate equivalent BSO, showing the potential applications in novel devices with photoluminescent/electrical multifunctional properties.     

Fault-tolerant control through dynamic surface triple-step approach for proton exchange membrane fuel cell air supply systems

Due to complex electrochemical and thermal phenomena, varying operations towards automotive applications, and vulnerable ancillaries in proton exchange membrane fuel cells (PEMFCs), fault diagnosis and fault-tolerant control (FTC) design have become important aspects to improve the reliability, safety and performance of PEMFC systems. This paper presents a novel FTC scheme for automotive PEMFC air supply systems via coordinated control of the air flow rate and the pressure in cathodes. A dynamic surface triple-step approach is first proposed considering nonlinear dynamics and the multi-input multi-output (MIMO) property, which combines the advantage of dynamic surface control in avoiding an “explosion of complexity” and the advantage of triple-step control in guaranteeing a simple structure and high performance. The normal case, the faulty case at the supply manifold and the faulty case in the back pressure valve are considered in the FTC design, with the stability of the overall system proved using Lyapunov methods. MATLAB/Simulink simulations with a high-fidelity PEMFC model verify the effectiveness of the proposed FTC scheme in regulating the air flow rate and oxygen excess ratio and maintaining the pressure of the cathode at a desired level even under faulty conditions.     

532 nm laser damage and nonlinear absorption of Cr2O72− doped KDP crystals

Potassium dihydrogen phosphate (KDP) single crystals doped with a series of trace dichromate (Cr₂O₇^2?) were prepared using “point seed” technique. The IR spectra suggest that the KDP crystal network becomes compact with trace of Cr₂O₇^2? while the lattice of crystal also can be destroyed by excessive doping. The UV–Vis spectra show that the transmittance percentage is descended of the doped KDP crystals. Z-scan analysis demonstrates that with increasing of Cr₂O₇^2? concentration, a gradual raise has been observed for the nonlinear absorption coefficient (β). The laser-induced damage threshold (LIDT) at 532 nm of the KDP crystal doped with 3000 ppm Cr₂O₇^2? is found to be 28.29 J/cm² which is higher than that of pure one under the R-on-1 model. However, as the doping concentration continues to increase, the LIDT decreases significantly. The variation of photoluminescence (PL) results is also consisted with the trend of LIDT for the doped samples. The LIDT of pyramidal sample is higher than that of prismatic one with the same doping concentration. The results suggest that the laser damage of doped crystal may be due to a synergistic effect of the concentration of micro defects and nonlinear absorption.     

DFT investigation analyzed with data mining technique of rare-earth dihydrides REH2 for hydrogen storage

Ab initio calculation and data mining are very useful methods to predict the interrelationships among structure properties. In this paper, the first-principles modelling based on the density functional theory (DFT) was used to explore the structural, mechanical, and electronic properties of ten hydrides REH₂ (RE = La, Ce, Pr, Nd, Sm, Tb, Dy, Ho, Er, Tm). From the present work, it can be noted that LaH₂, CeH₂, NdH_2, and PrH₂ compounds crystallizing in the hydrogen-rich cubic phase present good mechanical properties which could be of use to future applications in hydrogen storage. Furthermore, the electronic structures were also evaluated to provide a deep insight regarding their trends and confirm the metallic character of these systems. While, HoH₂, DyH₂, ErH₂, TbH₂, TmH₂, SmH₂ hydrides are mainly hard and rigid systems with high values of the bulk modulus (B), shear modulus (G), Young's modulus (E), micro-hardness (H), and low values of B/G ratio. More significantly, the adopted principal component analysis (PCA) provided an advantageous technique in selecting and identifying the minimum of inputs variables necessary to capture all information of the systems.     

The effect of maturity and tissue on the ability of mid infrared spectroscopy to predict the geographical origin of banana (Musa Cavendish)

The objective of this study was to evaluate the effect of sample presentation (tissue type) and maturity (ripe and unripe) on the classification of banana (Musa Cavendish) samples sourced from two different geographical regions and analysed using mid infrared (MIR) spectroscopy. The coefficient of determination (R²) and the standard error of cross-validation (SECV) obtained using partial least squares discriminant analysis were 0.83 (0.33), 0.75 (0.25) and 0.94 (0.19) for the prediction of maturity, geographical origin and tissue type, respectively. No effect of either of type of tissue (e.g. pulp or peel) or maturity was observed. The results of this study demonstrated that MIR spectroscopy might be used to classify the origin of the banana samples at different degrees of ripeness. However, one of the limitations of this study is on the number of samples analysed and further validation must be recommended using samples from other sources, regions and harvest seasons.     

The production of volatile compounds in model casein systems with varying fat levels as affected by low-frequency ultrasound

The effects of low-frequency ultrasound on the production of volatile compounds in model casein protein systems containing various fat concentrations of 2%, 4% and 6% (w/w) were investigated. Ultrasound application was performed at 20 kHz for up to 10 min which corresponded to energy densities ranging from 9.54 to 190.8 J mL⁻¹. Similar volatile compounds were detected both in pure fat and mixtures of casein and fat (CF) systems. These volatiles belonged to the groups of aldehydes, ketones, esters, alcohols and hydrocarbons, which were the products of oxidation of lipids or protein degradation due to acoustic cavitation. The amount of fat in the casein systems had minor effects on the production of volatiles, whereas the production of volatile compounds was significantly affected by the ultrasound treatment. Short sonication times <5 min generated similar volatile profiles to the untreated samples. In contrast, prolonged sonication for 5 and 10 min considerably increased the production of volatile compounds and the amounts of fatty acids. Thus, the application of low–frequency ultrasound for short periods should be considered to minimise the production of volatile compounds which can ultimately affect the taste.     

基于多维时空的NPCA-PSR-IGM(1,1)组合模型的短时交通流预测

针对城市短时交通流序列非线性和混沌性的特点,为提高短时交通流的预测精度,该文提出一种基于多维时空的非线性主成分分析(NPCA)和相空间重构(PSR)的改进灰色(IGM(1,1))组合预测模型。首先,使用数据相关性的非线性主成分分析算法对多维交通流量序列进行时空降维,同时保留影响预测点的主要交通流量数据,从而提高建模的精...     

An Algorithm for Output Spectrum Analysis of Nonlinear System with Correlative Sources Based on Power Series

An algorithm for output spectrum analysis of nonlinear system with correlative sources is proposed. First, the output terms of nonlinear system are analyzed based on the power series. Then, the algorithm is proposed. In the proposed method, different terms with the same frequency are picked out and added together by considering different phases, and the amplitudes of the output spectrum are obtained from the summarized results. Two numerical examples are used to verify the proposed algorithm. It is found that the amplitudes of output spectrum vary with different combinations of phases. Finally, the proposed algorithm is applied to control the output spectrum. Results show that the output amplitude of a specific frequency can be suppressed through changing both the amplitudes and the phases of the input signals.     

Determination of the quality and purity characteristics of olive oils obtained from different regions of Turkey,depending on climatic changes

Virgin olive oils (VOOs) obtained from olives grown in different regions of Turkey under changing climatic conditions sometimes show different sensory and chemical properties. This study was planned to determine whether these deviations are due to climatic changes or not. For this purpose, five different olive varieties (Ayvalık, Memecik, Gemlik, Nizip Yağlık, Kilis Yağlık) of commercial importance were harvested from the provinces/districts (four different region) where cultivation is intense during the 2017/2018–2020/2021 harvest years. Every year, olive samples were collected from 3 orchards from 13 provinces/districts. One hundred and fifty-six samples were subjected to the purity, quality and sensory analysis. Basic climatic values (average, minimum and maximum temperature, humidity and precipitation) were examined for four consecutive years. All of the examined olive oil samples were determined within the legal limits in terms of fatty acid composition and fatty acid ethyl ester values. However, delta-7-stigmastenol value from the sterol composition was found to be above 0.5% in some samples in all the years studied (total 21 samples). Delta-7-stigmastenol values of olive oil samples varied between 0.16% and 1.14%. Multiple linear regression analysis was applied using a genetic algorithm-based inverse least squares method to determine whether there is a relationship between climate data and delta-7-stigmastenol values. According to this result, it has been determined that the delta-7-stigmastenol value is high when the annual average relative humidity is low and the annual average temperature is high. There is an urgent need to make forward-looking plans due to climate change.