In this study, we investigate and compare three advanced control strategies, Type-1 Fuzzy Logic Control (T1FLC), Interval Type-2 Fuzzy Logic Control (IT2FLC), and Artificial Neural Networks (ANN), applied to Doubly-Fed Induction Generators (DFIGs) in Wind Energy Conversion Systems (WECS). As wind energy plays an increasingly critical role in renewable power generation, efficient and robust control of DFIGs is essential to ensure grid stability, reliability, and optimal energy extraction under variable wind conditions. T1FLC offers simplicity and robustness but may suffer from limited adaptability. IT2FLC improves upon this by managing higher levels of uncertainty and noise through the use of fuzzy sets with an additional degree of freedom. ANN-based control, on the other hand, leverages data-driven learning and non-linear mapping to achieve high performance but may require significant training and tuning. Simulations conducted in MATLAB/Simulink evaluate the performance of each controller under dynamic wind profiles, measuring key metrics such as rotor speed regulation, electromagnetic torque response, and power output stability. This comparative study provides insights for selecting suitable control schemes for DFIG-based wind energy systems under varying operational conditions.
This research work focuses on the development of a novel MPPT controller for a photovoltaic (PV) system using a SunPower SPR-200-BLK module connected to a DC load through a DC-DC boost converter. The proposed system integrates a Third-Order Sliding Mode Control (TOSMC) algorithm with a fuzzy inference system, forming a hybrid control scheme called Fuzzy-TOSMC. One of the key motivations behind this approach is that traditional PV control systems often require prior knowledge of the parameters of the system. The Fuzzy-TOSMC operates independently of the parameters of the model and does not require a voltage sensor for the MPPT control, simplifying both the analysis and implementation. An experimental comparative study between the proposed Fuzzy-TOSMC and the conventional TOSMC method under similar operating conditions is tested successfully using a solar array simulator Chroma 62050 H and a dSPACE 1202 device. Experimental results highlight the superiority of the proposed approach with a dynamic response of around 63
Agricultural intensification is a key driver of biodiversity loss in Mediterranean agroecosystems, yet its effects on protected bat assemblages remain poorly documented in northern Africa. All six bat taxa recorded are legally protected in Algeria. Several of the recorded species are also covered by international conservation instruments for their European populations, while the probable North African endemic Plecotus cf. gaisleri is of particular biogeographic interest. We conducted a preliminary assessment of bat activity, diversity, and community composition at two representative agricultural sites—a low-input citrus orchard and an intensively managed vineyard—in northern Algeria. Acoustic monitoring was conducted from March to November 2023. A total of 349 acoustic contacts were recorded at the citrus orchard site and 74 at the vineyard site, corresponding to a 4.6-fold difference in observed activity. Negative binomial modelling indicated a substantially lower fitted contact rate at the vineyard than at the orchard (IRR = 0.215, 95% CI: 0.130–0.355). Monthly taxon richness and Shannon diversity were also higher at the orchard. The vineyard assemblage was strongly dominated by Pipistrellus kuhlii, whereas a more taxonomically diverse assemblage was detected at the orchard. NMDS suggested site-associated structuring of bat assemblages, and a paired PERMANOVA detected a significant difference between the two sampled sites (R² = 0.281, pseudo-F = 6.26, p = 0.004). No statistically significant difference in multivariate dispersion was detected (PERMDISP: F = 0.808, p = 0.100), although the small sample size limits the power of this diagnostic test. Although based on a single orchard–vineyard pair, these results suggest that the low-input orchard examined here may provide favourable conditions for a protected bat assemblage. Replicated multi-site studies are needed before generalizing this pattern to low-input perennial agroecosystems across North African farmland.
In this paper, we study a model of competition between plasmid-bearing and plasmid-free organisms in a chemostat, where the plasmid-bearing population produces an allelopathic toxin that is lethal to its plasmid-free competitor. The model incorporates general monotonic growth rate functions and distinct removal rates for both species. We provide a complete analysis of the existence and local stability of all steady states in the four-dimensional system. With identical removal rates and Monod-type growth functions, the model was previously investigated by Hsu and Waltman. They showed that the system could exhibit two positive equilibria and conjectured that one of them is locally asymptotically stable whenever it exists, while the other is unstable. We confirm this conjecture in the present work. By including the different removal rates, it is shown that one of the positive equilibria destabilizes with the emergence of a stable limit cycle through supercritical Hopf bifurcations. Moreover, the operating diagram, which describes some asymptotic behavior of the model by varying the operating parameters, is presented. The bifurcation diagram as a function of the input concentration illustrates the various types of bifurcations of equilibria and the coexistence either around a positive equilibrium or sustained oscillations.
In this research work, tin oxide nanoparticles (SnO2 NPs) was developed to assess its photocatalytic performance against degradation of Congo red (CR) azodye under UVA-light illumination. To achieve this objective, SnO2 NPs was designed and synthesized via a sol–gel method using stannous chloride and oxalic acid dihydrate as precursors. The un-calcined sample heated at 80 °C for 4 h (labled as SnO2-80) and calcined catalysts at 450 °C and 650 °C for 4 h (identified as SnO2-450 and 650 °C, respectively) were subsequently characterized by various description techniques such as SEM, TGA-MS, XRD and UV-vi-DRS for their physicochemical properties. Here, numerous methods have been explored to estimate the crystallite size and strain in the SnO2-450 using X-ray peak profile analysis. XRD findings disclosed the formation of crystalized tetragonal-type SnO2 phase with P42/mnm space groupe symmetry. All methods provide crystallite sizes within 20–30 nm for SnO-450 NPs, excluding for LSL model (69.30 nm) which proved to be invalid crystal. Therefore, H-W model is efficient and most accurate for examining microstructural characteristics, since it gave the highest value of R2 (0.9031) and a decreased intrinsic strain (2.2 × 10–3). Rietveld refinement, performed by HighScore plus software, on collected XRD patterns of SnO2-450 was robust and convergence was achieved, yielding to low Rp (9.39
