Search Results (245)

This paper presents an intelligent cascaded fractional-order proportional–integral (CFO-PI) control strategy optimized using a genetic algorithm (GA) for a 1.5 MW DFIG-based multi-rotor wind turbine (MRWT) system. The primary objective is to enhance operational performance and power quality. The proposed method is evaluated against the conventional direct power control scheme using a traditional PI regulator (DPC-PI) to demonstrate its effectiveness. Comparative analysis shows substantial performance improvements achieved by the CFO-PI approach. Specifically, active power ripple is reduced by 61.71% compared to DPC-PI, resulting in smoother power delivery and improved grid compatibility. In addition, the steady-state error of active power decreases by 72.60%, indicating improved tracking accuracy. For reactive power, a 52.03% reduction in ripple is observed, while current ripple is reduced by approximately 56%, reflecting enhanced waveform quality. These results highlight the CFO-PI controller’s capability to maintain better power quality and steady-state performance relative to conventional DPC-PI. Overall, the GA-optimized CFO-PI controller provides a promising alternative for improving dynamic performance and power quality in DFIG-based MRWT systems. Full article

The multirotor configuration unmanned aerial vehicle faces a significant challenge in simultaneously achieving long-range operation and high payload capacity. This paper investigates the power management strategy for a novel fuel–electric hybrid aircraft that incorporates lifting wings to reduce rotor load and a range-extend system to enhance energy supply. An equivalent consumption minimization strategy is developed to optimize, in real time, the power distribution between the internal combustion engine and the battery. The primary innovation of this paper lies in the application and rigorous validation of the equivalent consumption minimization strategy on this new aircraft configuration, which effectively minimizes total energy cost by optimally balancing fuel consumption and battery degradation, resulting in significantly reduced fuel usage and a more stable power output compared to conventional approaches. Full article

Lightweight multi-rotor unmanned aerial vehicles (UAVs) have shown great potential in flexible Earth observation, but they impose strict restrictions on payload, volume, and power consumption. Traditional pulse-Doppler synthetic aperture radar (SAR) systems offer high imaging performance but suffer from high peak power and large volume, making them unsuitable for lightweight UAV platforms. To meet the low-power demand, most existing lightweight UAV SAR systems adopt frequency-modulated continuous-wave (FMCW) schemes, which are compact and low cost yet limited by a low range resolution, poor anti-interference ability, and single imaging modes. Therefore, it is urgent to develop an SAR system that combines the high performance of pulse radar with the lightweight advantage of FMCW radar. To this end, this paper proposes a compact, low-power Ka-band pulse-Doppler SAR system for multi-rotor UAVs. With 1.2 GHz bandwidth and highly integrated RF and antenna design, the system achieves miniaturization and low power consumption while maintaining high-resolution imaging capability. Furthermore, two-step waveform error correction and a signal predistortion method are presented to compensate amplitude and phase errors and improve the purity of the transmitted signal. Experimental results show that the proposed system can obtain clear SAR images with a resolution better than 0.3 m, providing a practical high-performance pulse-SAR solution for lightweight UAV platforms. Full article

Significant advances in UAV subsystems, including flight control, communication, propulsion, and onboard energy storage, have accelerated interest in commercial UAV operations within civilian airspace. However, widespread deployment remains limited by unresolved safety concerns, particularly the risk posed by uncontrolled descent following in-flight failures. In such events, free-fall impact can result in severe damage to personnel and property underneath. This paper proposes a novel UAV safety system based on an autonomous chemically-inflated airbag designed to deploy during a rapid descent and attenuate impact forces. While prior UAV airbag systems have relied on compressed-gas canisters, the proposed chemically-actuated approach enables faster deployment and reduces volumetric integration requirements. Experimental testing demonstrates a reduction in impact force from 4638.8 N to 1562.76 N (approximately 66%), with airbag inflation occurring within a fraction of a second. Additionally, the added mass of the safety system remains within the payload capacity of the selected UAV platform. These results indicate that chemically-inflated airbag systems offer a promising solution for improving UAV safety and facilitating scalable civilian deployment. Full article

Low altitude logistics and aerial transport increasingly rely on multirotor unmanned aerial vehicles (UAVs) carrying slung payloads, where cable flexibility and load swing can degrade safety and delivery accuracy. This paper studies payload trajectory tracking for a dual-quadrotor cooperative slung-load system, targeting accurate tracking with swing suppression under thrust, attitude, and cable-tension limits. First, a payload-layer dynamic model is derived from d’Alembert’s principle with geometric cable constraints, and explicit tension reconstruction formulas are provided to enable direct enforcement of tension bounds. Building on this model, a payload-layer DEA nominal tracking controller is designed by applying dynamic extension to the tension-scalar channels and enforcing output-level linear error dynamics. To ensure real-time feasibility, a convex quadratic-programming (QP) projection layer minimally corrects the nominal command to satisfy thrust saturation, attitude-cone constraints, and cable-tension bounds. Moreover, an adaptive tuning control layer updates the DEA feedback gain and the projection weighting matrix within preset constraint limits based on energy residual and constraint-activation information, improving robustness and reducing manual tuning. Input-to-state stability is established under bounded disturbances and constraint-activation switching via a composite Lyapunov analysis. ROS–PX4–Gazebo simulations show low tracking error, suppressed swing, and sustained tension-limit compliance, validating the fusion controller. Full article

Large-scale forest pest management has traditionally relied on aerial spraying; however, increasing regulatory restrictions and environmental concerns have limited its application in many regions. Unmanned Aerial Spraying System (UASS) platforms for aerial spraying have developed intensively in the last decade for pesticide application in agricultural crops but remain scarcely explored within the forestry sector. This study evaluates the feasibility of UASS-based spraying platforms for forest pest control. We tested a multi-rotor agricultural UASS in two different forest conditions: broadleaf and conifer stands. Both biological and synthetic insecticides were sprayed against two contrasting forest pests, Lymantria dispar and Adelges laricis. Defoliation and infestation intensity were used to assess treatment efficacy post-application. Results indicated differences in operational productivity between forest stand types, with higher treatment efficacy observed for L. dispar. Despite the correct dosage delivered by the UASS, the target organism showed a limited biological response in the conifer pest. In conclusion the use of UASSs in forest ecosystems is conditioned by forest-specific factors; however, these technologies show potential to be aligned with interventions targeting early-stage pest outbreaks. Full article

Following the growing interest in small-scale unmanned aerial vehicles (UAVs), this paper presents a comprehensive conceptual design methodology for a modular ducted-fan aerial vehicle intended for research applications. Although ducted-fan configurations offer significant advantages over conventional multirotor platforms, particularly in urban, indoor, and human-interaction scenarios, the availability of affordable and customizable ducted-fan UAVs platforms suitable for scientific research remains limited. To address this gap, the paper details the complete design of the vehicle, including propeller aerodynamics and duct design, mechanical structure, actuation system, dynamic modeling, and control strategy. All major structural and aerodynamic components are fabricated using low-cost additive manufacturing, enabling rapid prototyping and high modularity. The vehicle’s performance is experimentally assessed through bench tests and indoor flight experiments, demonstrating stable flight and satisfactory attitude control. The presented work shows that a fully functional ducted-fan UAVs can be realized using commercial off-the-shelf electronics and exclusively 3D-printed components, and provides practical guidelines to replicate and adapt the proposed platform for advanced research in UAVs control, navigation, and autonomy. Full article

In multirotor unmanned aerial vehicle (UAV) GNSS/INS integrated navigation systems, a single filter such as the extended Kalman filter (EKF) or the error-state extended Kalman filter (ESKF) is commonly adopted. However, both methods have inherent performance limitations. The EKF suffers from significant linearization errors in highly nonlinear flight scenarios, leading to degraded estimation accuracy. Although ESKF achieves higher precision during steady flight, its model assumptions may no longer strictly hold during aggressive maneuvers, causing performance degradation in complex flight missions. To address the limitations of using a single filter, this study proposes a dynamic filter selection strategy under the interaction multi-filter (IMF) framework. The approach builds on the interactive multiple model (IMM) method and establishes a cooperative mechanism between EKF and ESKF. By computing the filter likelihoods at each time step and updating the probability switching matrix, the framework adaptively selects the optimal filter based on the current flight conditions. Simulation results demonstrate that the proposed IMF-based strategy effectively avoids the performance bottlenecks of individual filters. In highly nonlinear environments, it reduces linearization errors and suppresses divergence trends; compared with traditional ESKF, the proposed algorithm 3D RMSE is reduced by 57.2%, compared with the adaptive robust EKF (AREKF), the proposed approach reduces positioning errors by up to 21.3%. The results confirm that IMF-based adaptive switching between EKF and ESKF yields a robust, high-precision solution for UAV navigation in complex operational scenarios. Full article

This paper applies the recently developed Prediction-Based Control Barrier Functions (PB-CBFs) to the obstacle avoidance problem for multirotor air taxis in Urban Air Mobility (UAM). Unlike conventional Control Barrier Functions (CBFs), PB-CBFs incorporate escape path predictions into the formulation, facilitating safe controller design for dynamical systems with high relative degree and enabling safety under strict control constraints. We first review the PB-CBF framework, then formulate the safety requirements specific to the collision avoidance problem and derive the corresponding invariance conditions. Finally, we validate our approach through simulation of the obstacle avoidance scenario, demonstrating the efficacy of PB-CBFs in ensuring safety in UAM operations and providing additional insight into the mechanism by which predictions are leveraged to enforce safety. Full article

Floating-base robotic systems rely critically on their inertial geometry to maintain stability and regulate interaction forces in the absence of fixed ground constraints. Their control authority additionally depends on the placement and orientation of actuators relative to the center of mass, which determines the moment arms through which thrust or force inputs generate stabilizing actions. This paper develops a general theoretical framework showing that internal mass shifting provides a powerful, domain-independent mechanism for reshaping global system dynamics. Through geometric principles governing center-of-mass placement, moment-arm modification, and inertia redistribution, mass shifting enhances passive stability, reduces the torque induced by external disturbances, and improves the controllability of interaction-intensive tasks. The theory is first examined in a buoyancy-driven simulation of a two-mass floating body subjected to multi-sine wave excitation, which isolates the hydrostatic effects of center-of-mass displacement. To validate the generality of these principles, we further demonstrate their applicability in a radically different domain through real-world experiments on the AeroBull aerial robot, a multirotor platform equipped with an internal mass-shifting mechanism for aerial manipulation. Across both aquatic and aerial settings, mass shifting consistently improves stability, reduces control effort, and increases achievable interaction forces. These results establish internal mass redistribution as a platform-agnostic strategy for enhancing the stability and resilience of floating-base robots operating in uncertain and physically demanding environments. Full article

The energy efficiency and hover stability of unmanned aerial vehicles are critical factors, since improper battery utilization and unstable control are major sources of operational failures and accidents. The proportional–integral–derivative (PID) controller, which is applied in approximately 97% of multirotor unmanned aerial vehicle (UAV) systems, is widely used due to its simplicity; however, it is sensitive to external disturbances and often fails to ensure optimal energy utilization, resulting in reduced flight time. Therefore, the experimental investigation of advanced control methods in a real physical environment is well justified. The objective of the present research is the comparative evaluation of seven control strategies—PID, linear quadratic controller with integral action (LQI), model predictive control (MPC), sliding mode control (SMC), backstepping control, fractional-order PID (FOPID), and H∞ control—using a single-degree-of-freedom drone test platform in a MATLAB R2023b-Arduino hardware-in-the-loop (HIL) environment. Although the theoretical advantages and model-based results of the aforementioned control methods are well documented, the number of real-time comparative HIL experiments conducted under identical physical conditions remains limited. Consequently, only a small amount of unified and directly comparable experimental data is available regarding the performance of different controllers. The measurements were performed at a reference height of 120 mm under disturbance-free conditions and under wind loading with a velocity of 10 km/h applied at an angle of 45°. The controller performance was evaluated based on hover accuracy, settling time, overshoot, and real-time measured power consumption. The results indicate that modern control strategies provide significantly improved energy efficiency and faster stabilization compared to the PID controller in both disturbance-free and wind-loaded test scenarios. The investigations confirm that several advanced controllers can be applied more effectively than the PID controller to enhance hover stability and reduce energy consumption. Full article

Small multi-rotor UAVs face endurance limitations during long-range missions due to high rotor energy consumption and limited battery capacity. This paper proposes a folding-wing range extender integrating a sliding-rotating two-degree-of-freedom folding wing—which, when deployed, quadruples the fuselage length yet folds within its profile—and a tail-thrust propeller. The device can be rapidly installed on host small multi-rotor UAVs. During cruise, it utilizes wing unloading and incoming horizontal airflow to reduce rotor power consumption, significantly extending range while minimally impacting portability, operational convenience, and maneuverability. To evaluate its performance, a 1-kg-class quadrotor test platform and matching folding-wing extender were developed. An energy consumption model was established using Blade Element Momentum Theory, followed by simulation analysis of three flight conditions. Results show that after installation, the required rotor power decreases substantially with increasing speed, while total system power growth slows noticeably. Although the added weight and drag increase low-speed power consumption, net range extension emerges near 15 m/s and intensifies with speed. Subsequent parametric sensitivity analysis and mission profile analysis indicate that weight reduction and aerodynamic optimization can effectively enhance the device’s performance. Furthermore, computational fluid dynamics (CFD) analysis confirms the effectiveness of the dihedral wing design in mitigating mutual interference between the rotor and the wing. Flight tests covering five conditions validated the extender’s effectiveness, demonstrating at 20 m/s cruise: 20% reduction in total power, 25% improvement in endurance/range, 34% lower specific power, and 52% higher equivalent lift-to-drag ratio compared to the baseline UAV. Full article

In this study, the aerodynamic performance of single- and multi-rotor sail systems was numerically investigated under various inflow directions and array configurations using Computational Fluid Dynamics (CFD) simulations. For a single-rotor sail, the optimal spin ratio (SR) for each wind direction was derived from the energy efficiency index, and an appropriate spacing distance of 9D was identified, within the present steady-RANS framework, as a preliminary guideline based on wake-recovery characteristics. Using these findings, four array configurations were established to reflect the practical installation conditions of a medium-range (MR) tanker. The wake interference and aerodynamic performance variations in each configuration were quantitatively compared and analyzed. The results showed that the average lift in all arrays remained within ±1% of that of a single-rotor, and the 1 × 1 × 1 array exhibited the most stable performance. These findings confirm that the wake-based spacing design and wind direction-dependent SR optimization proposed in this study are crucial for maintaining aerodynamic stability and improving efficiency in multi-rotor sail systems. It is expected that the results of this study will contribute to establishing design guidelines and operational strategies for the practical applications of rotor sails on ships. Full article

Rapid and precise intervention in disaster and medical-aid scenarios demands aerial platforms that can both survey and physically interact with their environment. This study presents the design, fabrication, modeling, and experimental validation of a one-piece, 3D-printed quadcopter with an integrated six-degree-of-freedom aerial manipulator robotic arm tailored for emergency response. First, we introduce an ‘X’-configured multi-rotor frame printed in PLA+ and optimized via variable infill densities and lattice cutouts to achieve a high strength-to-weight ratio and monolithic structural integrity. The robotic arm, driven by high-torque servos and controlled through an Arduino-Pixhawk interface, enables precise grasping and release of payloads up to 500 g. Next, we derive a comprehensive nonlinear dynamic model and implement an Extended Kalman Filter-based sensor-fusion scheme that merges Inertial Measurement Unit, barometer, magnetometer, and Global Positioning System data to ensure robust state estimation under real-world disturbances. Control algorithms, including PID loops for attitude control and admittance control for compliant arm interaction, were tuned through hardware-in-the-loop simulations. Finally, we conducted a battery of outdoor flight tests across spatially distributed way-points at varying altitudes and times of day, followed by a proof-of-concept medical-kit delivery. The system consistently maintained position accuracy within 0.2 m, achieved stable flight for 15 min under 5 m/s wind gusts, and executed payload pick-and-place with a 98% success rate. Our results demonstrate that integrating a lightweight, monolithic frame with advanced sensor fusion and control enables reliable, mission-capable aerial manipulation. This platform offers a scalable blueprint for next-generation emergency drones, bridging the gap between remote sensing and direct physical intervention. Full article

Unmanned Aerial Vehicles (UAVs), particularly multirotor drones, require rigorous structural monitoring to ensure safe and reliable operation. Visual inspections are often inefficient and may miss early signs of damage. Even when faults are detected visually, effective repair requires contextual knowledge such as past repairs, part specifications, and supplier information. This study presents an implemented and experimentally validated closed-loop Product Lifecycle Management (PLM) system that integrates vibration-based structural health monitoring (SHM) with UAV maintenance workflows. A physical quadcopter platform is utilized to collect vibration data for training and testing under eight physically induced single-fault scenarios, including damaged propellers and loosened components. Deep learning models are trained on time-domain vibration data collected from onboard sensors to learn fault patterns and are then deployed in the proposed system for real-time fault classification. The GRU (Gated Recurrent Unit) model is selected for deployment due to its superior performance and lower computational cost and is integrated with a custom-developed UAV data repository within the Aras Innovator PLM platform. Experimental validation shows that the GRU model achieves 99.26% classification accuracy and a macro F1-score of 0.9917, confirming the reliability of the vibration-based fault detection approach. This end-to-end integration enables not only real-time fault detection but also lifecycle traceability, digital documentation, and data-driven maintenance decisions. Experimental validation across test runs confirms that the proposed system accurately detects structural faults and enables automated safety protocols and maintenance workflows. The system improves inspection efficiency and demonstrates how closed-loop PLM can move beyond static documentation to actively monitor, diagnose, and manage UAV health throughout its operational lifecycle. Full article