Wind-gust Compensation Algorithm based on High-gain Residual Observer to Control a Quadrotor Aircraft: Real-time Verification Task at Fixed Point

Wind is considered a strong disturbance for quadrotor aircrafts (UAV) when an outdoor task at a fixed point is carried out. The effect of wind produces a distortion on the attitude of the vehicle which is reflected on undesired longitudinal movements. This paper addresses a real-time implementation and design of a robust embedded control-observer based on a type high-gain observer algorithm for on-line estimation and compensation of external disturbances produced by wind gusts on an autonomous quadrotor aircraft. A real-time experimental implementation of embedded Residual High Gain algorithm control is proposed in order to eliminate the effects of real perturbations in the hover position of the UAV. A Lyapunov function was used to practical stability analysis the system. Also numerical simulations were carried out to estimate wind behavior by the use of Drydel mathematical wind model. The main contribution of this work is the implementation of a Residual High Gain Observer in an outdoor real-time experiment in presence of real wind gusts perturbations. The proposed embedded algorithm control improves the stabilization of an UAV in the presence of real wind gusts with average of 8 m/s. The proposed algorithm improved the UAV behavior as shown by the GPS position experimental results, decreasing the wind effect on the translational movement of the aircraft.

     

Correlated synthetic time series generation for energy system simulations using Fourier and ARMA signal processing

As the contribution of renewable energy grows in electricity markets, the complexity of the energy mix required to meet demand grows, likewise the need for robust simulation techniques. While decades of wind, solar, and demand profiles can sometimes be obtained, this is too few samples to provide a statistically meaningful analysis of a system with baseload, peaker, and renewable generation. To demonstrate the viability of an energy mix, many thousands of samples are needed. Synthetic time series generation presents itself as a suitable methodology to meet this need. For a synthetic time series to be statistically viable, several conditions must be met. The series generator must produce independent, identically distributed samples, each having the same fundamental properties as the original signal without duplicating it exactly. One approach for such a generator is training a surrogate model using Fourier series decomposition for seasonal patterns and autoregressive moving average (ARMA) models to describe time-correlated statistical noise about the seasonal patterns. When combined, the Fourier plus ARMA (FARMA) model has been shown to provide an infinite set of independent, identically distributed sample time series with the same statistical properties as the original data [1]. When considering an energy mix with renewable electricity production, several time series of energy, grid, and weather measurements are needed for each synthetic year modeled to statistically comprehend the efficiency of any given energy mix. This includes measurements of solar exposure, air temperature, wind velocity, and electricity demand. These cannot be considered independent series in a given synthetic year; for example, in summer months demand may be higher when solar exposure and air temperature are high and wind velocity is low. To capture and reproduce the correlations that might exist in the measured histories, the ARMA can further be extended as a Vector ARMA (VARMA). In the VARMA algorithm, covariance in statistical noise is captured both within a history as part of the autoregressive moving average and with respect to the other variables in the time series. In this work, the implementation of the Fourier VARMA in the RAVEN uncertainty quantification and risk analysis software framework [2] is presented, along with examples of correlated synthetic history generation. Finally, methods to extend synthetic signals to multiyear samples are presented and discussed.     

Evaluation of SIMCA and PLS algorithms to detect adulterants in canola oil by FT-IR

Adulteration of canola oil with four potential edible oils was analysed using FT-IR and chemometric methods. The adulterants (corn, peanut, soya bean and sunflower oils) were studied in four different proportions (canola oil + adulterant oils: 90 + 10, 95 + 5, 98 + 2 and 99 + 1 in volume). Excellent classification results were obtained when multi-class approaches were performed with a maximum error of 3%, using 1630 or 16 wavenumbers as variables. In the case of one-class approaches, the selection of variables (16 wavenumbers) was necessary, improving the classification error to 5%. The differences observed using the different methods were related to the nature of each model depending on how the boundaries are set in each of them, responding either to a PCA-based or PLS-based algorithm.     

Embedded Nickel-Mesh Transparent Electrodes for Highly Efficient and Mechanically Stable Flexible Perovskite Photovoltaics: Toward a Portable Mobile Energy Source

The rapid development of Internet of Things mobile terminals has accelerated the market's demand for portable mobile power supplies and flexible wearable devices. Here, an embedded metal-mesh transparent conductive electrode (TCE) is prepared on poly(ethylene terephthalate) (PET) using a novel selective electrodeposition process combined with inverted film-processing methods. This embedded nickel (Ni)-mesh flexible TCE shows excellent photoelectric performance (sheet resistance of ≈0.2–0.5 Ω sq⁻¹ at high transmittance of ≈85–87%) and mechanical durability. The PET/Ni-mesh/polymer poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS PH1000) hybrid electrode is used as a transparent electrode for perovskite solar cells (PSCs), which exhibit excellent electric properties and remarkable environmental and mechanical stability. A power conversion efficiency of 17.3% is obtained, which is the highest efficiency for a PSC based on flexible transparent metal electrodes to date. For perovskite crystals that require harsh growth conditions, their mechanical stability and environmental stability on flexible transparent embedded metal substrates are studied and improved. The resulting flexible device retains 76% of the original efficiency after 2000 bending cycles. The results of this work provide a step improvement in flexible PSCs.     

Efficient Visible-Light Driven Photothermal Conversion of CO2 to Methane by Nickel Nanoparticles Supported on Barium Titanate

Solar-driven methanation represents a potentially cost-efficient and environmentally friendly route for the direct hydrogenation of CO₂. Recently, photothermal catalysis, which involves the combination of both photochemical and thermochemical pathways, has emerged as a promising strategy for the production of solar fuels. For a photothermal catalyst to efficiently convert CO₂ under illumination, in the absence of external heating, effective light harvesting, an excellent photothermal conversion and efficient active sites are required. Here, a new composite catalyst consisting of Ni nanoparticles supported on barium titanate that, under optimal reaction conditions, is able to hydrogenate CO₂ to CH₄ at nearly 100% selectivity with production rates as high as 103.7 mmol g^–1 h^–1 under both UV–visible and visible irradiation (production rate: 40.3 mmol g⁻¹ h^–1) is reported. Mechanistic studies suggest that reaction mostly proceeds through a nonthermal hot-electron-driven pathway, with a smaller thermal contribution.     

Global Analysis of the Dynamics of a Piecewise Linear Vector Field Model for Prostate Cancer Treatment

Oncological therapies usually are applied intermittently, i.e., not continuously over time. In the periods in between, though, the cancer cells are usually left free to grow. This intermittency is a key issue in prostate cancer hormonal therapies based on androgen suppression. Here, we address this treatment modality by analyzing a piecewise smooth vector field approach. In fact, using the PSA (prostate-specific antigen) serum level as a control variable to switch between treatment and no-treatment periods of hormone therapy (androgen withdrawal), by means of typical parameter values, our theoretical analysis supports the idea that intermittent androgen suppression may prevent a prostate cancer relapse for a specific class of patients.

     

Solution mixing preparation of PVDF/ZnO polymeric composite films engineered for heterogeneous photocatalysis

Despite the efforts of the scientific community, carrying out photocatalyst immobilization so that industrial application of photocatalysis becomes economically feasible is still a challenge to be overcome. In this work, polyvinylidene fluoride (PVDF)/ZnO composites were prepared by solution mixing based on solid knowledge of membrane technology and with the help of a powerful experimental design for systematic evaluation of the interaction among variables. A strategy for variable screening was used, followed by a complete evaluation at two levels, leading to predictive models. As a result, photocatalyst amount, pore agent concentration, and wet thickness were the most significant in the target molecule discoloration. With this, it was possible to obtain a 40 and 186% enhancement in photocatalytic efficiency compared to previous results and simple photolysis, respectively. Finally, the samples were characterized by FTIR-ATR, XRD, and SEM and chemical, crystalline and morphological differences were observed both with nanoparticle and pore agent incorporation. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48417.     

A Concise Review on Nano-emulsion Formation by the Phase Inversion Composition (PIC) Method

Nano-emulsion formation by the phase inversion composition method is reviewed. The relationship between phase behavior and nano-emulsion formation is revised with emphasis on the key role of phase transitions involving changes in the sign of the curvature of the surfactant layer (inversion) via zero-average-curvature structures such as bicontinuous microemulsions or lamellar liquid crystalline phases. The different low-energy methods that can be involved in a nano-emulsification process at constant temperature are also discussed.     

Bioactive compounds and antioxidant activity from harvest to edible ripeness of avocado cv. Hass (Persea americana) throughout the harvest seasons

The influence of regular air cold storage (7 °C and 85 ± 5% RH) followed by ripening at shelf-life conditions (19–21 °C and 65 ± 5% RH), on bioactive compounds of Hass avocados was investigated. Results showed that the content of mannoheptulose and perseitol decreased significantly already during cold storage and ripening period. The fatty acid profile and contents of tocopherols (α- and β-tocopherol) and phytosterols (β-sitosterol, stigmasterol, campesterol) remained unchanged from day 0 to edible ripeness. Total phenolics, hydrophilic and lipophilic antioxidant capacity remained unchanged during cold storage and increased during the ripening period. At edible ripeness, significant amounts of phenolic acids, p-coumaric and caffeic and their derivatives were synthesised. Our results demonstrated that regular air cold storage for up to 37 days followed by ripening at shelf-life conditions enhances the phenolic compounds and mainly the hydrophilic antioxidant capacity without affecting the remaining bioactive compounds in Hass avocado.