Search Results (177)

Ensuring the safe operation of Unmanned Aerial Vehicles (UAVs) is crucial for both mission-critical and safety-critical tasks. In scenarios where UAVs must track airborne targets, they need to follow the target’s path while maintaining a safe distance, even in the presence of unmodeled dynamics and environmental disturbances. This paper presents a novel collision avoidance strategy for dynamic quadrotor UAVs during target-tracking missions. We propose a safety controller that combines a learning-based Control Barrier Function (CBF) with standard sliding mode feedback. Our approach employs a neural network that learns the true CBF constraint, accounting for wind disturbances, while the sliding mode controller addresses unmodeled dynamics. This unified control law ensures safe leader-following behavior and precise trajectory tracking. By leveraging a learned CBF, the controller offers improved adaptability to complex and unpredictable environments, enhancing both the safety and robustness of the system. The effectiveness of our proposed method is demonstrated through the AirSim platform using the PX4 flight controller. Full article

This paper presents a composite disturbance-tolerant control framework for quadrotor unmanned aerial vehicles (UAVs). By constructing an enhanced dynamic model that incorporates parameter uncertainties, external disturbances, and actuator faults and considering the inherent underactuated and highly coupled characteristics of the UAV, a novel robust adaptive sliding mode controller (RASMC) is designed. The controller adopts a hierarchical adaptive mechanism and utilizes a dual-loop composite adaptive law to achieve the online estimation of system parameters and fault information. Using the Lyapunov method, the asymptotic stability of the closed-loop system is rigorously proven. Simulation results demonstrate that, under the combined effects of external disturbances and actuator faults, the RASMC effectively suppresses position errors (<0.05 m) and attitude errors (<0.02 radians), significantly outperforming traditional ADRC and LQR control methods. Further analysis shows that the proposed adaptive law enables the precise online estimation of aerodynamic coefficients and disturbance boundaries during actual flights, with estimation errors controlled within ±10%. Moreover, compared to ADRC and LQR, RASMC reduces the settling time by more than 50% and the tracking overshoot by over 70% while using the ($tanh(·)$) approximation to eliminate chattering. Prototype experiments validate the fact that the method achieves centimeter-level trajectory tracking under real uncertainties, demonstrating the superior performance and robustness of the control framework in complex flight missions. Full article

The autonomous landing of unmanned aerial vehicles (UAVs) on moving platforms has potential applications across various domains. However, robust landing remains challenging because the detection reliability of UAVs decreases when the UAV is close to a moving platform. To address this issue, this paper proposes a novel landing strategy that ensures a high detection rate. First, a robust detectable region was established by considering the sensing range and maneuverability limitations of the UAV. Second, a vector field was designed to guide the UAV to the moving platform while remaining in a robust detectable region. Next, safe and accurate landings were achieved by considering the current velocity and vector field. The landing strategy was validated through outdoor flight experiments. A quadrotor equipped with a gimbal-mounted camera was used, and a fractal marker was attached to the moving platform for detection and tracking. When the moving platform moved at a speed of 2–4.3 m/s, the UAV successfully landed on the platform with a distance error of 0.4 m. Because of the robust detectable region and vector field, the detection was conducted with a high success rate (94.9%). Full article

This paper tackles the challenge of achieving robust and precise control for a novel quadrotor featuring continuously variable arm lengths (15 cm to 19 cm), enabling enhanced adaptability in complex environments. Unlike conventional fixed-geometry or discretely morphing unmanned aerial vehicles, this design’s continuous structural changes introduce significant complexities in modeling its time-varying moment of inertia. To address this, we propose a control strategy that decouples dynamic motion from the evolving geometry, allowing for the development of a robust control model. A sliding mode control algorithm, optimized using particle swarm optimization, is implemented to ensure stability and high performance in the presence of uncertainties and noise. Extensive MATLAB 2016 simulations validate the proposed approach, demonstrating superior tracking accuracy in both fixed and variable arm-length configurations, achieving root mean square error values of 0.05 m (fixed arms), 0.06 m (variable arms, path 1), and 0.03 m (variable arms, path 2). Notably, the PSO-tuned SMC controller reduces tracking error by 30% (0.07 m vs. 0.10 m for PID) and achieves a 40% faster settling time during structural transitions. This improvement is attributed to the PSO-optimized SMC parameters that effectively adapt to the continuously changing inertia, concurrently minimizing chattering by 10%. This research advances the field of morphing UAVs by integrating continuous geometric adaptability with precise and robust control, offering significant potential for energy-efficient flight and navigation in confined spaces, as well as applications in autonomous navigation and industrial inspection. Full article

Autonomous exploration is a fundamental challenge for various applications of unmanned aerial vehicles (UAVs). To enhance exploration efficiency in large-scale unknown environments, we propose a Fast Autonomous Exploration Framework (FAEM) designed to enable efficient autonomous exploration and real-time mapping by UAV quadrotors in unknown environments. By employing a hierarchical exploration strategy that integrates geometry-constrained, occlusion-free ellipsoidal viewpoint generation with a global-guided kinodynamic topological path searching method, the framework identifies a global path that accesses high-gain viewpoints and generates a corresponding highly maneuverable, energy-efficient flight trajectory. This integrated approach within the hierarchical framework achieves an effective balance between exploration efficiency and computational cost. Furthermore, to ensure trajectory continuity and stability during real-world execution, we propose an adaptive dynamic replanning strategy incorporating dynamic starting point selection and real-time replanning. Experimental results demonstrate FAEM’s superior performance compared to typical and state-of-the-art methods in existence. The proposed method was successfully validated on an autonomous quadrotor platform equipped with LiDAR navigation. The UAV achieves coverage of 8957–13,042 m³ and increases exploration speed by 23.4% compared to the state-of-the-art FUEL method, demonstrating its effectiveness in large-scale, complex real-world environments. Full article

Traditional multirotor UAVs (unmanned aerial vehicles) are inherently underactuated, with coupled position and attitude control, which limits their maneuverability in specific applications. This paper presents a fully actuated quadrotor design based on a swashplateless rotor mechanism. Unlike existing fully actuated UAV designs that rely on servo-driven tilt mechanisms, this approach minimizes additional weight and simplifies the structure, resulting in a more maintainable system. The design, modeling, and control strategies for the quadrotor are presented. Furthermore, we propose a decoupled control method to address the need for both fully actuated and underactuated modes. The control architecture employs parallel attitude and position control structures and decouples the two subsystems using a nonlinear dynamic inversion (NDI) method. A compensation module is introduced to address the constraints imposed by the maximum rotor deflection angle and the corresponding feasible force set. This compensation module actively adjusts the attitude to mitigate the saturation of the required thrust, effectively overcoming the impact of rotor deflection angle limitations on trajectory tracking performance. The approach facilitates seamless switching between fully actuated and underactuated modes, enhancing the system’s flexibility and robustness. Simulation and flight experiments demonstrate the effectiveness and performance of the proposed design. Full article

This study addresses the problem of attitude and altitude tracking for a quadrotor system in the presence of parameter uncertainties. The goal is to develop a robust control strategy that can handle the nonlinear, strongly coupled dynamics of the quadrotor. To achieve this, we propose a fractional-order sliding mode control (FOSMC) scheme, which is specifically designed to improve system performance under uncertain parameters. The FOSMC approach is combined with additional adaptive laws to further enhance the robustness of the control system. We derive the necessary control laws and apply them to the quadrotor’s state-space representation, ensuring that the system remains stable and performs accurately in the presence of uncertainties. Numerical simulations are conducted to evaluate the effectiveness of the proposed control strategy. The results show that the FOSMC-based controller successfully achieves precise tracking of both attitude and altitude, demonstrating significant robustness against parameter variations and disturbances. In conclusion, the proposed FOSMC scheme provides a reliable solution for controlling quadrotor systems in uncertain environments, offering the potential for real-world applications in autonomous UAV operations. Full article

Unmanned Aerial Vehicles (UAVs) have become indispensable across various industries, but their efficiency, particularly in multirotor designs, remains constrained by aerodynamic limitations. This study investigates the integration of airfoil shapes into the arms of multirotor UAV frames to enhance aerodynamic performance, thereby improving energy efficiency and extending flight times. By employing Computational Fluid Dynamics (CFD) simulations, this research compares the aerodynamic characteristics of a standard quadrotor frame against an airfoil-integrated design. The results reveal that while airfoil-shaped arms marginally increase drag in cruise flight, they significantly reduce downforce across all flight conditions, optimizing thrust utilization and lowering overall energy consumption. The findings suggest potential applications in military reconnaissance, agriculture, and other fields requiring longer UAV flight durations and improved efficiency. This work advances UAV design by demonstrating a feasible method for enhancing the performance of multirotor systems while maintaining structural simplicity and cost-effectiveness. Full article

Aiming at the problem of the nonlinear, strongly coupled, and underdriven trajectory tracking instability of a quadrotor unmanned aerial vehicle (UAV), this thesis proposes a feedback linearization and fractional order model predictive control strategy based on feedback linearization by modeling the dynamics of the UAV control system and linearizing the nonlinear model of attitude control. A dual closed-loop control structure, feedback linearization control (FLC) for a position loop, and fractional order model predictive control (FOMPC) for an attitude loop are adopted to realize fast position tracking and attitude response. In addition, considering that the fractional order method has the advantage of flexible regulation, the fractional order integral operator is added to the cost function of model predictive control. Finally, the simulation results and the calculation of the root mean square error verify that the proposed method has a fast response speed, small overshoot, stable flight, and good track tracking performance in UAV track tracking. Full article

This paper presents the simulation and controller optimization of a quadrotor Unmanned Aerial Vehicle (UAV) system. The quadrotor model is derived adopting the Newton-Euler approach, and is intended to be constituted by four three-phase Permanent Magnet Synchronous Motors (PMSM) controlled with a velocity control loop-based Field Oriented Control (FOC) technique. The Particle Swarm Optimization (PSO) algorithm is used to tune the parameters of the PID controllers of quadrotor height, quadrotor attitude angles, and PMSMs’ rotational speeds, which represent the eight critical parameters of the PMSM-quadrotor UAV system. The PSO algorithm is designed to optimize eight Square Error (SE) cost functions which quantify the error dynamics of the controlled variables. For each stabilization task, the PID tuning is divided in two phases. Firstly, the PSO optimizes the error dynamics of altitude and attitude angles of the quadrotor UAV. Secondly, the desired steady-state rotational speeds of the PMSMs are derived, and the PSO is used to optimize the motors’ dynamics. Finally, the complete PMSM-Quadrotor UAV system is simulated for stabilization during the target task. The study is carried out by means of simulations in MATLAB/Simulink^®. Full article

The growing use of quadrotor unmanned aerial vehicles (UAVs), especially in low-altitude airspace, has raised concerns about their susceptibility to high-intensity radiated fields (HIRFs). These electromagnetic interferences can significantly affect UAV performance and safety. Therefore, understanding the electromagnetic behavior of quadrotor UAVs in HIRF environments and establishing robust airworthiness standards is crucial. In this paper, a novel transfer function model specifically designed for small quadrotor UAVs in HIRF environments is studied, covering the frequency range from 100 MHz to 6 GHz. The model characterizes the relationship between internal electric field strength and frequency in response to external excitation conditions. A comprehensive simulation of the interference with UAVs in the HIRF environment is conducted, followed by test validation in an anechoic chamber. To assess the consistency between simulation and test results, the feature selection validation (FSV) method is employed. This paper also compares the UAV transfer function with that of a conventional aircraft, revealing the unique electromagnetic characteristics of quadrotor UAVs and offering insights into their vulnerability in HIRF environments. The findings provide valuable contributions to the development of UAV airworthiness certification standards and their safe operation in complex electromagnetic environments. Full article

Motion planning is critical for ensuring precise and efficient operations of unmanned aerial vehicles (UAVs). While polynomial parameterization has been the prevailing approach, its limitations in handling complex trajectory requirements have motivated the exploration of alternative methods. This paper introduces a finite Fourier series (FFS)-based trajectory parameterization for UAV motion planning, highlighting its unique capability to produce piecewise infinitely differentiable trajectories. The proposed approach addresses the challenges of fixed-time minimum-snap trajectory optimization by formulating the problem as a quadratic programming (QP) problem, with an analytical solution derived for unconstrained cases. Additionally, we compare the FFS-based parameterization with the polynomial-based minimum-snap algorithm, demonstrating comparable performance across several representative trajectories while uncovering key differences in higher-order derivatives. Experimental validation of the FFS-based parameterization using an in-house quadrotor confirms the practical applicability of the FFS-based minimum-snap trajectories. The results indicate that the proposed FFS-based parameterization offers new possibilities for motion planning, especially for scenarios requiring smooth and higher-order derivative continuity at the expense of minor increase in computational cost. Full article

The advancement of drone technology has underscored the critical need for adaptability and enhanced functionality in unmanned aerial vehicles (UAVs). Morphing quadrotors, capable of dynamically altering their structure during flight, offer a promising solution to extend and optimize the operational capabilities of conventional drones. This paper presents a comprehensive review of current advancements in morphing quadrotor research, focusing on morphing concept, actuation mechanisms and flight control strategies. We examine various active morphing approaches, including the integration of smart materials and advanced actuators that facilitate real-time structural adjustments to meet diverse mission requirements. Key design considerations—such as structural integrity, weight distribution, and control algorithms—are meticulously analyzed to assess their impact on the performance and reliability of morphing quadrotors. Despite their significant potential, morphing quadrotors face challenges related to increased design complexity, higher energy consumption, and the integration of sophisticated control systems. The discussion on challenges and opportunities highlights the necessity for ongoing advancements in morphing quadrotor technologies, particularly in addressing adaptive control problems associated with highly nonlinear and dynamic morphing aircraft systems, and in the potential integration with smart materials. By synthesizing the latest research and outlining prospective directions, this paper aims to serve as a valuable reference for researchers and practitioners dedicated to advancing the field of morphing quadrotor technologies. Full article

The construction of a six-degree-of-freedom (6-DOF) model for the composite motion of the actual mechanical structure (defined as an all-true composite motion model) of unmanned aerial vehicles (UAVs) is a prerequisite for achieving stable control of rotorcraft UAVs. Therefore, this paper proposes a construction approach for a nonlinear 6-DOF model of quadrotor and dual-rotor coaxial UAVs based on all-true composite motion. Two types of attitude–altitude control systems for rotorcraft based on a self-optimizing intelligent proportional–integral–derivative (PID) control method are constructed. Three-dimensional geometric models of the two rotorcraft types, incorporating their physical characteristics, are built. The attitude responses to different pulse width modulation (PWM) inputs are tested, thereby verifying the accuracy of the all-true composite model and analyzing the stability of the two types of UAVs. Furthermore, two types of attitude–altitude control inner loop controllers are designed, and the intelligent PID control algorithm is used to optimize the control parameters. Further verification of the robustness of the optimized parameters is carried out, and the designed attitude controllers are verified via experiment using a turntable. The simulation and experimental results show that the proposed all-true composite motion model and controller design method can accurately simulate the dynamic characteristics of the two types of UAVs and maintain stable attitude control, thus providing a valuable reference for the accurate attitude control of rotorcraft UAVs based on all-true composite motion. Full article

This paper introduces a stable adaptive PID-like control scheme for quadrotor Unmanned Aerial Vehicle (UAV) systems. The PID-like controller is designed to closely estimate an ideal controller to meet specific control objectives, with its gains being dynamically adjusted through a stable adaptation process. The adaptation process aims to reduce the discrepancy between the ideal controller and the PID-like controller in use. This method is considered model-free, as it does not require knowledge of the system’s mathematical model. The stability analysis performed using a Lyapunov method demonstrates that every signal in the closed-loop system is Uniformly Ultimately Bounded (UUB). The effectiveness of the proposed PID-like controller is validated through simulations on a quadrotor for path following, ensuring accurate monitoring of the target positions and yaw angle. Simulation results highlight the performance of this control scheme. Full article