Search Results (1,539)

In this work, an adaptive event-triggered-based consensus control strategy is proposed for the quadrotor unmanned aerial vehicle (QUAV) formation system in the presence of external disturbances and state constraints. Firstly, the disturbed QUAV formation system dynamic model is established. Then, to address the initial peaking explosion problem in the traditional active disturbance rejection control method, a time-varying gain extended state observer (TGESO) is designed to suppress external disturbances. Meanwhile, a novel barrier Lyapunov function (BLF) is constructed to cope with the adverse effects caused by state constraints. Furthermore, aiming to alleviate network congestion and reduce communication burden, the adaptive event-triggered mechanism (AETM) is adopted to design the formation flight controller. Finally, the stability of the developed consensus controller and the boundedness of all error signals are proved via Lyapunov theory. Comparative simulation results demonstrate the practicality of the presented control algorithm. Full article

The Upper Colorado River Basin (UCRB), through the process of snow accumulation, to snowmelt, to streamflow runoff, provides a critical water source to approximately 40 million residents in the Southwestern United States. Given the importance of late fall–winter–early spring (October, November, December, January, February, March, or ONDJFM), cumulative precipitation, future estimates of ONDJFM cumulative precipitation, and potential drought occurrence would provide a benefit to water managers and planners. Previous research efforts successfully reconstructed (extended the period of record) the regional April 1st Snow Water Equivalent (SWE) in the UCRB using tree-ring chronologies and reconstructed climate (El Niño–Southern Oscillation or ENSO). The current research efforts differ by (a) incorporating future [Shared Socioeconomic Pathway (SSP) 5-8.5] predictions of ONDJFM cumulative precipitation (in lieu of April 1st SWE) at a single station location (Kendall R.S.) in the UCRB; (b) reconstructing ONDJFM cumulative precipitation (in lieu of April 1st SWE) using tree-ring chronologies and ENSO; and (c) evaluating an alternative reconstructed ENSO index. The reconstructed record, recent past observations, and future (SSP 5-8.5) ONDJFM cumulative precipitation were then combined to provide a paleo perspective of future drought. Results indicate that extreme ONDJFM cumulative precipitation drought periods projected for the ~2040s were exceeded in the reconstructed record. A pattern of alternating wet and dry conditions was also identified, consisting of a wet (pluvial) period in the 2030s, followed by drought conditions in the 2040s, and another wet period in the 2050s. Many of the extreme future wet (pluvial) periods exceeded those in the recent record and reconstructed record. Full article

Permanent magnet synchronous motors (PMSMs) are utilized in demanding conditions and applications requiring precision and accuracy, such as servo systems. Especially at low speeds, the effects of cogging torque, current measurement and offset errors, improper controller gains, mechanical resonance, and torque fluctuations caused by load torque and flux result in fluctuations at various frequencies in the motor output speed. This study, motivated by two factors, proposes an extended state observer (ESO)-based multivariable fast response extremum-seeking (FESC) interval type-2 fuzzy PID (IT2FPID) controller to improve dynamic response and reduce speed ripple at low speeds in situations where all these negative factors could arise. This approach enables the real-time adaptation of parameters to counteract the decline in controller performance caused by the nonlinear characteristics of PMSMs and parameter fluctuations while also optimizing disturbance rejection in the speed response under varying operating conditions and existing speed ripple. The experimental results from the prototype setup validate that the proposed control mechanism is functional, valid, and precise in diminishing speed ripples during low-speed operations. The simulation and test outcomes of the control scheme show that speed noise at low speeds is reduced from 26% to 3% compared to traditional proportional-integral (PI) controller and supertwisting (STW) sliding mode controller (SMC) responses and that the scheme exhibits a 16–23% reduction in undershoot amplitude and faster recovery in the presence of load torque variations. Full article

Ice accretion poses a threat to fixed-wing aerial vehicles as it alters the wings’ shape and thus degrades the aerodynamic performance. In manned aircraft, the icing detection system assists the pilot and utilises dedicated sensors. However, in unmanned aerial vehicles (UAVs), onboard icing detection can generally only be achieved using standard sensors in conjunction with dynamical models, because dedicated sensors are rarely available. In this paper, we propose two approaches based on the particle filter for both icing detection and accurate state and aerodynamic parameter estimation in the presence of icing, with different levels of severity. The first approach uses the observation likelihood for icing hypothesis testing with a complement of the Gaussian kernel to compute icing probability. The second approach uses a discrete jump approach based on a Bernoulli process and a subset of particles to test the icing hypothesis for faster icing detection by estimating changes in icing-related aerodynamic parameters. Using both approaches, the simulation results demonstrate improved estimation accuracy compared to an extended Kalman filter (EKF), under both moderate and severe icing conditions. With adequate tuning, the proposed approaches show potential for indirect icing detection in UAVs. They also enable the computation of icing severity and provide a more accurate and reliable estimate of the icing probability compared to the EKF. Full article

To address the calibration challenge caused by the nonlinear variation in intrinsic parameters during continuous camera zooming in UAV electro-optical pods, this paper proposes an online calibration method based on IMU-visual fusion. Traditional offline calibration cannot adapt to dynamic scenarios, while existing self-calibration methods suffer from slow convergence and insufficient robustness. The proposed method aims to achieve real-time and accurate estimation of camera intrinsic parameters during zooming. Specifically, we first construct a unified state estimation framework that encodes the internal and external parameters of the camera and the 3D positions of scene feature points into a high-dimensional state vector, then establish a camera motion model based on IMU data, construct a visual observation model by combining the pinhole camera and second-order radial distortion model to establish a nonlinear mapping from 3D feature points to 2D pixel coordinates, and adopt an improved ORB algorithm for feature extraction and LK optical flow method to achieve high-precision cross-frame feature matching to enhance the stability of visual observation. Most importantly, we design a tight-coupling fusion strategy based on the Extended Kalman Filter (EKF) prediction-update iteration mechanism, which fuses IMU high-frequency motion constraints and visual geometric constraints in real time to suppress parameter drift induced by focal length changes. Finally, we recursively solve the state vector to complete the online dynamic estimation of intrinsic parameters. Monte Carlo simulation experiments and real UAV flight experiments confirm that the method has both high estimation accuracy and strong environmental adaptability, can meet the high-precision calibration needs of UAVs in dynamic scenarios, and provides reliable technical support for accurate target positioning. Full article

Tidal energy is increasingly harnessed due to its high energy density, substantial reserves, and reliable predictability. However, marine fouling on turbine blades adds weight and induces asymmetric system loads; prolonged operation exacerbates generator magnetic saturation, causing inductance parameter deviations from controller presets, which further leads to current loop delays, amplified tracking errors and unstable power output. To mitigate these issues, a self-tuning inductance-oriented model-free predictive current control method is proposed. The proposed method utilizes a simplified hyperlocal model alongside an extended state observer to effectively counteract the effects of non-inductive parameters. Simultaneously, the incremental model coupled with a dynamic adjustment method is proposed for real-time adaptive inductance tuning. Simulation results demonstrate that the proposed method significantly enhances system robustness against inductance mismatches and reduces parameter sensitivity, thereby ensuring stable operation. Compared with traditional PI control and model predictive control strategies, the proposed approach exhibits superior performance in disturbance rejection, parameter adaptability, and operational stability. Full article

This paper presents a comprehensive framework for the identification, state estimation, and robust control of a bistable Duffing–Holmes oscillator, validated through an experimental setup. First, to address parametric uncertainty, a Recursive Least Squares Method (RLSM) with a forgetting factor is applied to a filtered model representation, enabling accurate parameter convergence from noisy measurements. Subsequently, a Nonlinear Integral Extended State Observer (NIESO) is designed to reconstruct unmeasured states and estimate total disturbances. A key theoretical contribution is the derivation of explicit gain conditions that guarantee the observer’s stability, overcoming limitations of previous designs. For trajectory tracking, an observer-based backstepping controller is synthesized. Crucially, to bridge the gap between theory and practice, a drift-free integration scheme is implemented to generate feasible position commands for the shake table, preventing actuator saturation. Experimental results confirm the framework’s effectiveness, achieving a 3.7-fold reduction in RMS tracking error compared to open-loop operation, with the tracking error rapidly converging to a small neighborhood within approximately $0.2$ $\mathrm{s}$. Furthermore, the closed-loop system demonstrates superior energy efficiency, requiring significantly lower actuator voltage to sustain stable interwell oscillations. Full article

Background: Parents of school-age children with neurodevelopmental and conduct difficulties face elevated stress, reduced self-efficacy and relational strain, yet evidence for scalable, school-embedded support remains limited. Drawing on mentalization theory—which emphasises parents’ capacity to understand behaviour in terms of underlying mental states—this mixed-methods study evaluated a weekly parent learning group integrating psychoeducation, mentalization-based practice and peer support, delivered within an alternative provision school. Methods: A group of twelve parents who attended at least six sessions completed retrospective pretest–posttest questionnaires assessing parental reflective functioning (PRFQ) and parenting self-efficacy (PSOC). Semi-structured interviews explored parents’ subjective experiences and perceived changes in parent–child interactions and parent–school relationships. Quantitative outcomes were analysed using paired t-tests and effect sizes; qualitative data underwent reflexive thematic analysis. Results: Quantitative analyses revealed statistically significant improvements in parental reflective functioning and self-efficacy. Pre-mentalizing scores decreased substantially (d = 1.34), indicating reductions in non-mentalizing, while interest and curiosity about children’s mental states increased markedly (d = 1.83). Parenting self-efficacy improved significantly (d = 1.61). Although a reduction in excessive certainty about mental states approached significance (d = 0.63, p = 0.053), trends suggested greater epistemic balance. Qualitative analysis identified six themes elucidating mechanisms of change, including enhanced mentalizing capacity, reduced parental stress, transformed parent–child interactions and facilitation style as a critical active ingredient. Integration of findings suggests that psychoeducational content provided conceptual grounding for understanding behaviour, facilitator modelling scaffolded reflective practice, and relational safety within the group enabled authentic engagement with challenging experiences. Conclusions: These preliminary findings indicate that a school-based parent learning group combining psychoeducation, mentalization-based practice and peer support is feasible and associated with meaningful improvements in parental reflective functioning and self-efficacy. Parent narratives of transformed relational practices and shifts from reactive to reflective engagement echo broader literature demonstrating that group-delivered mentalization-oriented programmes can enhance reflective capacities and caregiving quality in diverse family contexts. The school setting may extend the reach of such interventions to families not engaged with clinical services and support collaborative parent–school partnerships. Future research should employ larger, controlled designs, incorporate observational and child outcome measures, and explore scalability across educational contexts. Full article

The fabrication of NiTiZr alloys by solid-state routes remains challenging due to limited atomic diffusion and the high reactivity of Ti and Zr. Mechanical alloying offers a potential pathway for synthesising such systems; however, complete alloy formation is not always achieved under practical milling conditions. Researchers have infrequently explored the mechanical alloying of NiTiZr, and this study systematically investigates the effect of milling time on microstructural evolution rather than claiming complete alloy synthesis. A high-energy planetary ball mill was used to mechanically process elemental powders of Ni, Ti, and Zr for 5–28 h. The examination revealed that longer milling times resulted in progressive crystallite refinement and increased lattice strain, while particle morphology evolved from irregular to more globular shapes due to repeated fracture and cold welding. After 28 h of milling, limited reacted regions containing Ni, Ti, and Zr were observed (~4.6% area fraction), while most of the powder remained heterogeneous and polyphasic, with no evidence of complete Ni₅₀Ti₃₀Zr₂₀ alloy formation. X-ray diffraction showed significant peak broadening without systematic 2θ peak shifts, indicating severe plastic deformation and crystallite refinement rather than definitive solid-solution formation of the allot. Differential scanning calorimetry revealed exothermic thermal events between 300 °C and 470 °C, which are attributed to defect recovery and thermally activated structural rearrangements rather than confirmed martensitic or crystallisation transformations. These results demonstrate that high-energy ball milling alone is effective for particle size reduction and defect generation but insufficient for producing a fully homogeneous Ni₅₀Ti₃₀Zr₂₀ alloy within 28 h. Additional activation energy, such as post-milling heat treatment or extended processing, is required to promote complete alloying in this system. Full article

Meningitis remains a significant cause of morbidity and mortality in the United States despite advances in vaccination, antimicrobial therapy, and critical care. However, long-term national mortality patterns across demographic and geographic subgroups remain incompletely characterized. This study evaluated temporal trends in meningitis-associated mortality among U.S. adults aged ≥25 years from 1999 to 2024 using the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) Multiple Cause of Death database. Death certificates listing meningitis as either the underlying cause or a contributing cause of death were identified using ICD-10 codes to capture meningitis-associated mortality. Age-adjusted mortality rates (AAMRs) per 100,000 population were calculated using the 2000 U.S. standard population. Temporal trends were assessed using Joinpoint regression to estimate annual percent change (APC) and average annual percent change (AAPC). Across the study period, meningitis-associated mortality demonstrated an early decline followed by stabilization and more recent increases in several subgroups. AAMRs decreased significantly from 1999 to 2001 (APC: −14.09%; p = 0.0029) and from 2001 to 2013 (APC: −4.74%; p < 0.000001), followed by a significant increase from 2013 to 2024 (APC: 1.78%; p = 0.0059). Despite these later increases, the overall AAPC across the full study period remained significantly negative (AAPC: −2.73%; p < 0.000001). Earlier analyses using shorter observation windows did not demonstrate a statistically significant overall trend; the significance observed in the present analysis reflects the inclusion of extended mortality data through 2024. Mortality rates were consistently higher among males and adults aged ≥65 years. Non-Hispanic Black individuals experienced increasing mortality after 2013, while Hispanic individuals demonstrated a sustained increase across the entire study period. Regional analyses showed recent increases in the Northeast, South, and West, while non-metropolitan areas did not experience statistically significant improvement through 2020. In summary, meningitis-associated mortality among U.S. adults declined significantly during the early study years but has shown stabilization and recent increases in several demographic and geographic subgroups since approximately 2013. Although overall mortality across the full study period remains lower than baseline levels, these emerging disparities highlight the importance of continued surveillance and targeted public health interventions. Full article

The environmental pressure simulation facility is crucial to the development and testing of high-performance aeroengines. During environmental pressure simulation tests of aeroengines, a large amount of uncertain high-temperature and low-pressure gas is discharged into the pressure regulation system, resulting in significant disturbances and complex coupling among compressor unites, valves and the main pipe. To analyze the surge mechanism and support controller design, a control-oriented dynamic model of pressure regulation system is established. By considering the dominant pressure dynamics of the main pipe and the dynamic characteristics of compressors and regulating valves, the original complex system is simplified into a nonlinear model suitable for control analysis and safety-oriented design. Based on the developed model, the safe operation problem of compressor units is transformed into a constrained control problem. A cooperative sliding mode control (Co-SMC) method is then proposed to ensure that the compressor pressure ratio remains within a safe range while mitigating the impact of exhaust disturbances on the pressure regulation process. The proposed method enhances the robustness of pressure regulation system and the grid-connected efficiency of compressor units while guaranteeing the stability of closed-loop system. Comparative simulations under complex operating conditions demonstrate that the proposed method significantly improves both the safety level and control performance of pressure regulation system. Full article

Fixed-wing unmanned aerial vehicles, with their advantages of long endurance and substantial payload capacity, are poised to be a key platform for the future low-altitude economy. However, the challenge of achieving precise attitude tracking control under unknown time-varying disturbances persists. To tackle this difficulty, this article introduces a soft-sign function-based active disturbance rejection control (SSADRC) method, and develops a hybrid grey wolf optimizer (HGWO) with balanced exploration–exploitation mechanisms for intelligent parameter tuning. Specifically, SSADRC utilizes a novel smooth nonlinear function with saturation constraints to reconstruct the nonlinear feedback controller and the extended state observer, ensuring smooth and stable control output. Subsequently, HGWO integrates the good point set-based initialization strategy, the fitness-based dynamic-weight strategy, the diversity-based adaptive-mutation strategy, and the logistic chaotic map-based survival-of-the-fittest strategy, addressing the tuning of multiple coupled parameters in SSADRC. Additionally, the SSADRC-based pitch attitude controller is designed for a fixed-wing unmanned aerial vehicle, and an HGWO and seven other swarm optimization algorithms are employed to tune the parameters. The results demonstrate that the HGWO exhibits the best convergence accuracy in the SSADRC parameter optimization task, and SSADRC illustrates better command tracking performance and state estimation accuracy than typical ADRC. Full article

Drawing on the Seeking Proxies for Internal States (SPIS) model and the concept of Difficulties in Accessing Internal States (DAIS), the present study examined the statistical associations among self-esteem, DAIS, body-checking, and disordered eating patterns (DEP). Within the SPIS framework, self-esteem is conceptualized as an evaluative internal state that may be appraised through externally observable proxies, such as body appearance. Cross-sectional data were collected from 200 adults recruited through Prolific Academic. Hayes’ PROCESS macro was used to test simple and serial mediation models examining whether DAIS and body-checking statistically account for associations between state self-esteem and DEP. Lower self-esteem was associated with higher DEP. Both DAIS and body-checking statistically accounted for portions of this association in simple mediation models. In a serial mediation model, the fully sequential pathway (self-esteem → DAIS → body-checking → DEP) remained statistically significant after accounting for shared variance among mediators. Given the cross-sectional design, these findings cannot establish temporal or causal relationships, but the observed pattern of associations is compatible with the proposed conceptual process. Additionally, our findings are based on a nonclinical sample and reflect variability in subclinical eating pathology. Implications for extending the SPIS framework to dimensional eating-related phenomena are discussed. Full article

In wireless power transfer (WPT) systems, magnetically coupled wireless power transfer has become a major research focus due to its advantages such as long transmission distance, strong tolerance to misalignment, and high power transfer capability. It is also widely applied in vehicle wireless power transfer systems. From the perspective of practical engineering applications, this paper investigates the problem of system parameter variations caused by changes in inductance and load, in combination with magnetically coupled structures. During actual system operation, misalignment of the coupling mechanism leads to variations in mutual inductance, while the load resistance may also fluctuate. These parameter changes result in alterations to the overall output characteristics of the system, which are detrimental to stable system operation. Moreover, adopting a dual-side communication control strategy is susceptible to interference from the system’s power circuitry. To address these issues, this paper proposes a novel state variable modeling method and designs a state observer based on the extended Kalman filter (EKF) algorithm to estimate the secondary-side parameters, thereby enabling observation of the voltage across the load at the receiver side. The state observer is configured with two operating modes to monitor variations in mutual inductance and load resistance. The observer outputs are compared with the actual load-side voltage, and the effectiveness of the proposed state observer is verified. Full article

This review summarizes recent experimental progress in the structure and correlations of light neutron-rich nuclei. We first highlight achievements based on quasi-free scattering reactions in inverse kinematics at the Radioactive Isotope Beam Factory (RIBF), including investigations of the single-particle composition of halo systems—for example, revealing the minimal s-wave component in the “weak-halo” nucleus ¹⁷B—and the mapping of universal, surface-localized dineutron correlations in Borromean nuclei such as ¹¹Li, ¹⁴Be and ¹⁷B. We then discuss recent advances in the study of multineutron correlations and cluster states, addressing both experimental challenges and major breakthroughs. These include the observation of a candidate $4n$ resonance, the absence of a resonant state in the $3n$ system, the characterization of direct two-neutron decay in ¹⁶Be, and evidence for a condensate-like $\alpha +{}^{2}n+{}^{2}n$ cluster structure in the ${}^8\mathrm{He}\left(0_2^{+}\right)$ state. Finally, we discuss prospects for extending such investigations to heavier halo candidates and more complex multineutron systems, and outline the development of next-generation neutron detector arrays that will drive future progress in this field. Full article